Abstract: Description of the project and the findings

The dataset in question is of used cars in a popular catalog from the country of Belarus. This dataset will be cleaned and analyzed, to answer several questions about the effect that certain variables have on the price point at which cars are sold at. Ultimately, Multiple Linear Regression Models, SVR, Decision Tree Regression, Random Forest Regression, and KNN will all be used to predict the market price of a used car in Belarus given the attributes found in the dataset. The accuracy of these models were analyzed and performance tested for real-world application with the help of a training and testing dataset. Afterwords, the models were compared to find the most effective model for predicting the price of a used car in Belarus. STATE OUR FINDINGS

Introduction: Overview of the problems/goals and how they will be solved

We went through many datasets to find the one we were all interested in. We chose this dataset because it had a significant amount of samples, and there was a mixture of continuous and categorical variables. Since cars are such a big investment we all wondered what affected the price on cars. This is what sparked our initial questions and goals. Solving our proposed questions and goal we hope to gain insights in what affects car prices which would leave us with more knowledge we can use later in life. To solve our questions and answer our goal we are going to use R to make graphs to answer our questions. We will make sure to use different statistical analyses to make sure our graphs are confirmed to be accurate.

Initial Questions

The main goal is to create a predictive model based on insights gained from analyzing the impact of variables on the selling price of a vehicle. The goal was chosen for its applicability and general interest of which attributes impact price of a used car. In addition, there will be several questions that will be answered concerning the dataset. These questions aid in solving the main goal and are important insights to be gleaned from the dataset. The questions that will be answered about the dataset are as follows:

Data Analysis and Modeling:

Visualizations used to analyze data

In an attempt to gain a robust knowledge of our dataset several visualizations were used. Visualization of our data was done in two sections. Initially each attribute was graphed in order to gain a general understanding of how the samples are distributed for each attribute. This was done with the help of Bar Graphs, Histograms, Boxplots, the count function, and pie graphs.

# 1)What is the distribution of manufacturers?
ggplot(cars_edited, aes(y = manufacturer_name)) + geom_bar(aes(fill = manufacturer_name)) + geom_text(stat='count', aes(label=..count..), hjust=1)

# We can see a large difference in the amount cars for each manufacturers. Volkswagen, Opel, BMW, Audio, AvtoVAZ, Ford, Renault, and Mercedes-Benz are the majot manufacturers.
# 2) A table to show unique car model names and quantity
View(cars_edited %>% count(model_name))

# 3) Plotting the number of cars with automatic or mechanical transmissions
transmissionGrouped <- group_by(cars_edited, transmission)
transmissionCounted <- count(transmissionGrouped)
percentTransmission <- paste0(round(100*transmissionCounted$n/sum(transmissionCounted$n), 2), "%")
pie(transmissionCounted$n, labels = percentTransmission, main = "Transmission Distribution", col = rainbow(nrow(transmissionCounted)))
legend("right", c("Automatic", "Mechanical"), cex = 0.8,
       fill = rainbow(length(transmissionCounted)))

# Mechanical is significantly more common than Automatic. This will definitely be an attribute to consider in our final model
# 4) Plotting cars by color and quantity
ggplot(cars_edited, aes(x = color)) + geom_bar(stat = "count", aes(fill = color)) + geom_text(stat = "count", aes(label = after_stat(count)), vjust = -1)

# There is a lot of diversity in the colors and once again although there are categories with more values there is still a decent amount of variation

# 5) Histogram Odometer Value: Graph to see how the data is skewed
ggplot(cars_edited, aes(odometer_value)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# The data is left-skewed with what appears to be outliers as around 1,000,000 miles

# 6) Histogram Year produced: Graph to see how the data is skewed
ggplot(cars_edited) + geom_histogram(aes(year_produced))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# The graph seems to almost be normally distributed minus what appears to be some outliers on the the older end of the years
# 7) Graph to show what fuel distribution
ggplot(cars_edited, aes(x = engine_fuel)) + geom_bar(stat = "count", aes(fill = engine_fuel)) + geom_text(stat = "count", aes(label = after_stat(count)), vjust = -1)

# There are only 2 major engine fuels(gasoline and diesel)
# 8) Pie graph to show engine type Distribution (Electric, Diesel, Gasoline)
TypeGrouped <- group_by(cars_edited, engine_type)
TypeCounted <- count(TypeGrouped) 
percentType <- paste0(round(100*TypeCounted$n/sum(TypeCounted$n), 2), "%")
pie(TypeCounted$n, labels = percentType, main = "Engine Type Distribution", col = rainbow(nrow(TypeCounted)))
legend("right", c("diesel", "electric", "gasoline"), cex = 0.8,
       fill = rainbow(nrow(TypeCounted)))

# Not surprisingly gasoline and diesel are the 2 most common Engine Type considering the fuel distribution

# 9) Table for Engine capacity
View(cars_edited %>% count(engine_capacity))
# Engine Capacity seems to be left-skewed which may indicate outliers

# 10) Bar graph Body type: count how many cars have the same body type
ggplot(cars_edited, aes(x = body_type), stat = "count") + geom_bar() + geom_text(stat = "count", aes(label = after_stat(count)), vjust = -1)

# There is some diversity in body type and the diversity in categories may lend itself to useful data for a future model

# 11) Graph Drivetrain distribution:
drivetrainGrouped <- group_by(cars_edited, drivetrain)
drivetrainCounted <- count(drivetrainGrouped) 
percentdrivetrain <- paste0(round(100*drivetrainCounted$n/sum(drivetrainCounted$n), 2), "%")
pie(drivetrainCounted$n, labels = percentdrivetrain, main = "Drivetrain Distribution", col = rainbow(nrow(drivetrainCounted)))
legend("right", c("all", "front", "rear"), cex = 0.8,
       fill = rainbow(nrow(drivetrainCounted)))

# Although most vehicles are front wheel drive there is enough all and real wheel drive to gather some promising insights 

# 12) Number of cars with same price
ggplot(cars_edited, aes(x = price_usd), stat = "count") + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# This graph is extremely left-skewed. The sheer usefulness of price in our dataset will make this our main response attribute.

# 13) Pie Graph exchangeability Distribution
exchangeableGrouped <- group_by(cars_edited, is_exchangeable)
exchangeableCounted <- count(exchangeableGrouped) 
percentexchangeable <- paste0(round(100*exchangeableCounted$n/sum(exchangeableCounted$n), 2), "%")
pie(exchangeableCounted$n, labels = percentexchangeable, main = "Exchangeability Distribution", col = rainbow(nrow(exchangeableCounted)))
legend("right", c("False", "True"), cex = 0.8,
       fill = rainbow(nrow(exchangeableCounted)))

# Exchangeability is more common than anticipated. It will be interesting to see if pricier or cheaper cars consent to exchanges
# 14) Pie Graph Location region: Count the number of cars in a region
regionPriceDF <- group_by(cars_edited, location_region)
regionPriceDFCount <- count(regionPriceDF)
percentRegion <- paste0(round(100*regionPriceDFCount$n/sum(regionPriceDFCount$n), 2), "%")
pie(regionPriceDFCount$n, labels = percentRegion, main = "Region Price Distribution", col = rainbow(nrow(regionPriceDFCount)))
legend("right", c("Brest Region", "Gomel Region", "Grodno Region", "Minsk Region", "Mogilev Region", "Vitebsk Region"), cex = 0.8,
       fill = rainbow(nrow(regionPriceDFCount)))

# Minsk accounts for a very large amount of vehicles(makes sense considering the population sizes) with even distributions everywhere else. 
# The usefulness of the attribute may be less since Minsk is such a large portion of the data.
# 15) Histogram Number of photos: Graph to see how the data is skewed
ggplot(cars_edited) + geom_histogram(mapping = aes(number_of_photos))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# Graph is very left-skewed. I suspect photos may increase the value of a vehicle, but tests will need to be done on this

# 16) Box plot Number of photos: Graph to see how the data is skewed
ggplot(cars_edited) + geom_boxplot(mapping = aes(number_of_photos))

# There are many outliers. With extra time we may be able to investigate the impact of these outliers on the data.

# 17) Histogram Up counter: investigating how our outliers look with our modifications
ggplot(cars_edited) + geom_histogram(mapping = aes(up_counter))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

# Clearly an outliers exists since there is a large scale. 

# 18) Box plot Duration listed: investigating how our outliers look with our modifications
ggplot(cars_edited) + geom_boxplot(mapping = aes(duration_listed))

# There is a significant amount of outliers. There is no evidence to conclude these should be eliminated.

# 19) Histogram Duration listed: Graph to see how the data is skewed
ggplot(cars_edited) + geom_histogram(aes(duration_listed))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Once a general understanding of each attribute was gained we began to visualize various combinations of attributions. These visualizations were vital in seeing different relationships among our samples. The visualizations that were used were Balloon Plot, Scatterplot, frequency polygons, dplyr::summarize, and Boxplots.

# 1) Graph to show the amount of cars(by manufacturer name) in a region BALLOON PLOT
ggplot(cars_edited, aes(location_region, manufacturer_name)) + geom_count()

# Due to the quantity of categories a test will need to be done to gather significant data
# 2) Graph to show the price of a car according to its year produced SCATTER PLOT
ggplot(cars_edited, aes(year_produced, price_usd)) + geom_point() + geom_smooth()
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

# There exists a parabolic relationship between year_produced and price_usd

# 3) Graph to show the number of cars in specific colors(10 red cars, 8 blue cars etc.) by region BAR GRAPH
ggplot(cars_edited, aes(color)) + geom_bar(aes(fill = location_region))

# From looking at the bar graph there does not seem to be any significant differences in color distribution for locations

# 4) Graph to show the price of a car according to it's millage(odometer) SCATTER PLOT
ggplot(cars_edited, aes(odometer_value, price_usd)) + geom_point(aes(color = is_exchangeable)) + geom_smooth()
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

# This graph is incredible diverse and indicates that there is a need for advanced models to access price relationships.

# 5)Graph to show the price of a car according to it's year produced AND body type SCATTER PLOT
ggplot(cars_edited, aes(year_produced, price_usd)) + geom_point(aes(color = body_type)) + geom_smooth()
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

# There seems to be a parabolic relationship between year_produced and price_usd

# 6) Group by car body type and get it's mean price
group_by(cars_edited, body_type) %>% summarise(price_mean = mean(price_usd))
## # A tibble: 12 x 2
##    body_type price_mean
##    <chr>          <dbl>
##  1 cabriolet     10976.
##  2 coupe          7458.
##  3 hatchback      4036.
##  4 liftback       7873.
##  5 limousine      8154.
##  6 minibus        8466.
##  7 minivan        6131.
##  8 pickup        11748.
##  9 sedan          5782.
## 10 suv           13768.
## 11 universal      5017.
## 12 van            6675.
# 7) Graph to show the outliers with body type and price BOX PLOT
ggplot(cars_edited) + geom_boxplot(mapping = aes(x = reorder(body_type, price_usd), y =
                                                   price_usd))

# 8) Graph to show the correlation between car body type, price, AND engine fuel
ggplot(cars_edited) + geom_point(mapping = aes(x = body_type, y = price_usd, color = engine_fuel))

# 9) Graph to show the price of a car according to it's number of photos incl. engine fuel SCATTER PLOT
ggplot(cars_edited) + geom_point(mapping = aes(x = number_of_photos, y = price_usd, color = engine_fuel))

# 10) Group cars by manufacturer, and get it's mean price
cars_edited %>% group_by(manufacturer_name) %>% summarize(mean(price_usd)) %>% View()

Several machine learning techniques were used in an attempt to create the most accurate prediction model. The models used in the project were as follows:

Multiple Linear Regression: This was used for the sake of gauging the impact of the continuous attributes on the price of the vehicle. This model is simple to understand and involves less computing power than more advance models which led to our decision to utilize this ML method as our first model.

SVR: Used to see if there is a model that can handle every attribute and adjust the model according to its impact on price. Although this model involves much more computing power we believed that the robust nature of this model lends itself to a high level of accuracy. This models effectiveness with categorical data, and ability to work with both linear and non-linear boundaries makes it a prime model for our dataset. Furthermore, in order to optimize our SVR model we will use linear, polynomial, and radial kernel transformations and compare the results from the models that we generate.

Decision Tree (Partition): Used for predictive modeling. Since it is incredibly robust and relies on very few assumptions we believed it would be able to handle possible outliers in our data and work around the size of our dataset to produce an optimal model. Its simpler nature also makes it a model that would be preferred over other models(such as Random Forest Regression or KNN).

Random Forest Regression: Albeit, Random Forest Regression is more complicated than a Decision Tree since it leverages multiple decision trees it is still a crucial model for our dataset. The reason for using this model is for the sake of seeing if we can create an even more accurate model. If we find the accuracy is marginally better it may be preferred to use a Decision Tree since its easier to compute. Nevertheless, the Random Forest Regression is a wonderful tool in creating a predictive model and worth testing out for the sake of optimization.

KNN:K Nearest Neighbor was chosen due to its popularity and simplicity. KNN is able to handle our Categorical as well as Continuous attributes and for that reason it is a good model to be used to predict price. It will be vital to compare this model with the other models to investigate how useful of a model it is for our dataset.

Final outcomes and Analysis

Questions and Answer Justifications

Q1: What impact does a region have on price?

A: Although the region does impact price the extent of this impact would have to be assessed in a model that includes more attributes. The reason for this is because correlation does not necessitate causation. In other words, more attributes may be at play and to get a better understanding of the impact of region on price it will be vital to access the role region has in the overall models.

Justification:

To answer this question we decided to use a bar chart in order to see the average prices per region in comparison with each other.

Looking at the graph we can predict that region may play a part in price. We derive this prediction from the observation that although most regions have similar vehicle price averages Minsk has a significantly higher average. However, we can’t conclude that with just this graph, we need to confirm this by an appropriate test. The test used to see if region did in fact have a significant impact of price was the One-Way Anova Test. Anova was used because the region attribute consists of several categories and we wished to see its impact on a single continuous variable.

Prior to doing the One-Way Anova test we first performed some data transformation to gain a better understanding of the differences between the region prices.

group_by(regionPriceDF, regionPriceDF$location_region) %>%
  summarise(
    count = n(),
    mean = mean(price_usd, na.rm = TRUE),
    sd = sd(price_usd, na.rm = TRUE)
  )
## # A tibble: 6 x 4
##   `regionPriceDF$location_region` count  mean    sd
##   <chr>                           <int> <dbl> <dbl>
## 1 Brest Region                     2989 5091. 4652.
## 2 Gomel Region                     3140 5022. 4603.
## 3 Grodno Region                    2485 4745. 4223.
## 4 Minsk Region                    24193 7668. 7117.
## 5 Mogilev Region                   2678 4622. 4654.
## 6 Vitebsk Region                   3005 4870. 4450.

Once again quick inspection tells us that Minsk has a significantly different price and a much larger count. To affirm our suspicions from the graph and summarize we now perform the Anova test.

The hypotheses for the test are as follows:

H0 = The means of the different groups are the same

Ha = At least one sample mean is not equal to the others

Furthermore, we will use 0.05 as our significance level. The result of the anova test was the following:

# Compute the analysis of variance
res.aov <- aov(regionPriceDF$price_usd ~ regionPriceDF$location_region,
               data = regionPriceDF)
# Summary of the analysis
summary(res.aov)
##                                  Df    Sum Sq   Mean Sq F value Pr(>F)    
## regionPriceDF$location_region     5 7.020e+10 1.404e+10   355.9 <2e-16 ***
## Residuals                     38484 1.518e+12 3.945e+07                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Looking at the results of the one-way anova we can confirm our prediction. The p-value was less than 0.05(<2e-16) and so we conclude that there are significant differences between the regions.

We continue our investigation of the problem at hand by using Tukey HSD to do multiple pairwise-comparisons between the means of our groups.

# Tukey Test
TukeyHSD(res.aov)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = regionPriceDF$price_usd ~ regionPriceDF$location_region, data = regionPriceDF)
## 
## $`regionPriceDF$location_region`
##                                      diff        lwr          upr     p adj
## Gomel Region-Brest Region       -69.35261  -526.7479   388.042672 0.9980976
## Grodno Region-Brest Region     -346.16487  -832.0693   139.739598 0.3250300
## Minsk Region-Brest Region      2576.92905  2229.9066  2923.951471 0.0000000
## Mogilev Region-Brest Region    -468.67476  -944.9226     7.573076 0.0567405
## Vitebsk Region-Brest Region    -220.94393  -683.3226   241.434780 0.7500113
## Grodno Region-Gomel Region     -276.81226  -757.3836   203.759111 0.5708661
## Minsk Region-Gomel Region      2646.28166  2306.7669  2985.796388 0.0000000
## Mogilev Region-Gomel Region    -399.32215  -870.1275    71.483215 0.1502298
## Vitebsk Region-Gomel Region    -151.59132  -608.3623   305.179697 0.9345414
## Minsk Region-Grodno Region     2923.09392  2546.0489  3300.138960 0.0000000
## Mogilev Region-Grodno Region   -122.50989  -621.0582   376.038406 0.9819607
## Vitebsk Region-Grodno Region    125.22095  -360.0959   610.537820 0.9775888
## Mogilev Region-Minsk Region   -3045.60381 -3410.1197 -2681.087958 0.0000000
## Vitebsk Region-Minsk Region   -2797.87298 -3144.0722 -2451.673795 0.0000000
## Vitebsk Region-Mogilev Region   247.73083  -227.9175   723.379142 0.6744633

Analyzing the results we can conclude that the differences in average price between Minsk and every other region is statistically significant. The data set region does have an impact on vehicle price.

Q2: What is the distribution of manufacturers and whether manufacturers have a significant impact on the asking price of a vehicle?

A: We can confirm that there is a relationship between the manufacturer and asking price. The relationship seems to be one of the larger factor for asking price, but is not significant enough to predict price on its own.

Justification:

Two bar graphs were used in solving this question. First a bar graph was used to plot the distribution of vehicles for each manufacturer. Then another bar graph was used as a means of quickly inspecting how average price ranged between different manufacturers. As useful as these graph were in understanding the relationship between price and manufacturer it proved to be insufficient in proving a result. In order to prove that there existed a significant relationship between manufacturer and asking price of a car One-Way Anova was utilized. Once again were were dealing with a categorical data with several categories which lends the problem nicely to this sort of test.

First a bar graph was used to effectively plot the distribution of vehicles for each manufacturer.

# 1)What is the distribution of manufacturers?
ggplot(cars_edited, aes(y = manufacturer_name)) + geom_bar(aes(fill = manufacturer_name)) + geom_text(stat='count', aes(label=..count..), hjust=1)

Once the distribution of the Manufacturers was plotted we turned our attention onto the second part of the question: Whether manufacturers have a significant impact on the asking price of a vehicle?

Another bar graph was used as a means of quickly inspecting how average price ranged between different manufacturers.

manuPriceDF <- group_by(cars_edited, manufacturer_name)
manuPriceDF_averages <- summarise(manuPriceDF, average_price_usd = mean(price_usd))
ggplot(manuPriceDF_averages, aes(x = average_price_usd, y = manufacturer_name)) + geom_bar(aes(fill = manufacturer_name),stat="identity") + geom_text(aes(label =  paste0("$",round(average_price_usd)), hjust = 1))

Looking at the bar graph we can predict that the manufacturer of a vehicle has an impact on asking price. Nevertheless, observation is not sufficient evidence and so we proceed by testing this claim. Once again we are dealing with categorical data and we wish to compare the means of the prices for the Manufacturers. Naturally we chose the One-Way Anova test to test our claim.

The hypotheses for the test are as follows:

H0 = The mean prices of the different groups are the same

Ha = At least one sample mean price is not equal to the others

Furthermore, we will use 0.05 as our significance level. The result of the anova test was the following:

manuSumm <- group_by(manuPriceDF, manuPriceDF$manufacturer_name) %>%
  summarise(
    count = n(),
    mean = mean(price_usd, na.rm = TRUE),
    sd = sd(price_usd, na.rm = TRUE)
  )

# Compute the analysis of variance
res.aovTwo <- aov(manuPriceDF$price_usd ~ manuPriceDF$manufacturer_name,
                  data = manuPriceDF)

summary(res.aovTwo)
##                                  Df    Sum Sq   Mean Sq F value Pr(>F)    
## manuPriceDF$manufacturer_name    54 2.917e+11 5.402e+09   160.1 <2e-16 ***
## Residuals                     38435 1.297e+12 3.374e+07                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Investigating the results of the one-way anova we can confirm our claim. The p-value was less than 0.05(<2e-16) and so we conclude that there are significant differences between the manufacturers.

We continue with the Tukey HSD to do multiple pairwise-comparisons between the means of our groups. This will allow us to see exactly which manufacturers significantly differ in asking price.

# Tukey Test
TukeyHSD(res.aovTwo)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = manuPriceDF$price_usd ~ manuPriceDF$manufacturer_name, data = manuPriceDF)
## 
## $`manuPriceDF$manufacturer_name`
##                                   diff           lwr           upr     p adj
## Alfa Romeo-Acura         -10084.335812 -13398.412816  -6770.258809 0.0000000
## Audi-Acura                -5617.940986  -8542.074322  -2693.807650 0.0000000
## AvtoVAZ-Acura            -11253.964620 -14331.390271  -8176.538970 0.0000000
## BMW-Acura                 -3220.773360  -6142.847952   -298.698768 0.0098274
## Buick-Acura                 103.433240  -4371.192712   4578.059192 1.0000000
## Cadillac-Acura            -1679.761258  -6274.337531   2914.815015 1.0000000
## Chery-Acura               -8226.907806 -12446.430142  -4007.385470 0.0000000
## Chevrolet-Acura           -3899.753914  -6996.282248   -803.225579 0.0004993
## Chrysler-Acura            -7777.394129 -10886.804139  -4667.984118 0.0000000
## Citroen-Acura             -8337.560393 -11283.736949  -5391.383838 0.0000000
## Dacia-Acura               -7430.134384 -11630.580762  -3229.688005 0.0000000
## Daewoo-Acura             -11196.277176 -14484.878716  -7907.675636 0.0000000
## Dodge-Acura               -7164.873956 -10355.247478  -3974.500435 0.0000000
## Fiat-Acura                -9762.865630 -12762.013245  -6763.718015 0.0000000
## Ford-Acura                -7775.208586 -10697.930086  -4852.487086 0.0000000
## GAZ-Acura                 -8883.154009 -12211.222572  -5555.085446 0.0000000
## Geely-Acura               -5003.653374  -9012.297969   -995.008779 0.0006279
## Great Wall-Acura          -6349.125631 -11206.653264  -1491.597998 0.0001830
## Honda-Acura               -6257.789435  -9260.701961  -3254.876909 0.0000000
## Hyundai-Acura             -4846.695515  -7816.604124  -1876.786905 0.0000001
## Infiniti-Acura             1021.719029  -2401.828492   4445.266551 1.0000000
## Iveco-Acura               -2720.568787  -6225.148759    784.011185 0.5590565
## Jaguar-Acura               5040.114091    715.951749   9364.276432 0.0031536
## Jeep-Acura                -1860.396470  -5529.818019   1809.025079 0.9993157
## Kia-Acura                 -4616.790383  -7605.188489  -1628.392276 0.0000007
## LADA-Acura                -5174.204539  -8651.630940  -1696.778139 0.0000028
## Lancia-Acura              -9871.377540 -13653.199454  -6089.555625 0.0000000
## Land Rover-Acura           2422.414471   -941.365166   5786.194108 0.7538364
## Lexus-Acura                4357.674936   1054.901794   7660.448078 0.0001401
## Lifan-Acura               -4492.349739  -8966.975691    -17.723787 0.0471910
## Lincoln-Acura             -3035.413687  -7892.941320   1822.113946 0.9561928
## Mazda-Acura               -8041.358808 -10998.001161  -5084.716455 0.0000000
## Mercedes-Benz-Acura       -3383.068837  -6311.131868   -455.005806 0.0038085
## Mini-Acura                  360.814973  -3690.205026   4411.834972 1.0000000
## Mitsubishi-Acura          -7353.423719 -10344.779418  -4362.068021 0.0000000
## Moskvitch-Acura          -11793.973727 -16074.308968  -7513.638487 0.0000000
## Nissan-Acura              -6361.371736  -9316.316508  -3406.426964 0.0000000
## Opel-Acura                -8346.893009 -11267.007102  -5426.778917 0.0000000
## Peugeot-Acura             -8390.668183 -11325.931250  -5455.405115 0.0000000
## Pontiac-Acura             -8409.341861 -13036.919107  -3781.764616 0.0000000
## Porsche-Acura              5856.937861   1693.008174  10020.867549 0.0000196
## Renault-Acura             -8213.662237 -11137.428803  -5289.895672 0.0000000
## Rover-Acura              -11038.643696 -14304.640542  -7772.646850 0.0000000
## Saab-Acura                -8642.300539 -12305.235359  -4979.365718 0.0000000
## Seat-Acura                -8904.870563 -12089.495659  -5720.245467 0.0000000
## Skoda-Acura                 953.187554  -2021.345703   3927.720810 1.0000000
## SsangYong-Acura           -5053.563504  -8963.204678  -1143.922330 0.0002493
## Subaru-Acura              -5250.791304  -8447.139313  -2054.443295 0.0000000
## Suzuki-Acura              -7470.287148 -10737.813833  -4202.760464 0.0000000
## Toyota-Acura              -2974.733453  -5935.978455    -13.488451 0.0467818
## UAZ-Acura                 -9329.762125 -13299.068324  -5360.455927 0.0000000
## Volkswagen-Acura          -6345.125089  -9253.294780  -3436.955397 0.0000000
## Volvo-Acura               -4356.544370  -7371.536467  -1341.552272 0.0000079
## ZAZ-Acura                -11412.674719 -16040.251964  -6785.097473 0.0000000
## Audi-Alfa Romeo            4466.394826   2769.939003   6162.850650 0.0000000
## AvtoVAZ-Alfa Romeo        -1169.628808  -3118.463133    779.205518 0.9771695
## BMW-Alfa Romeo             6863.562452   5170.657696   8556.467208 0.0000000
## Buick-Alfa Romeo          10187.769052   6399.671376  13975.866728 0.0000000
## Cadillac-Alfa Romeo        8404.574555   4475.511342  12333.637767 0.0000000
## Chery-Alfa Romeo           1857.428007  -1625.641808   5340.497822 0.9977701
## Chevrolet-Alfa Romeo       6184.581899   4205.720025   8163.443773 0.0000000
## Chrysler-Alfa Romeo        2306.941684    307.982654   4305.900714 0.0039024
## Citroen-Alfa Romeo         1746.775419     12.600431   3480.950407 0.0449530
## Dacia-Alfa Romeo           2654.201429   -805.734463   6114.137320 0.5923139
## Daewoo-Alfa Romeo         -1111.941364  -3379.606834   1155.724106 0.9997048
## Dodge-Alfa Romeo           2919.461856    796.753728   5042.169985 0.0000403
## Fiat-Alfa Romeo             321.470183  -1501.245651   2144.186016 1.0000000
## Ford-Alfa Romeo            2309.127227    615.106106   4003.148348 0.0000532
## GAZ-Alfa Romeo             1201.181803  -1123.349753   3525.713359 0.9989183
## Geely-Alfa Romeo           5080.682439   1856.300625   8305.064253 0.0000003
## Great Wall-Alfa Romeo      3735.210181   -498.344035   7968.764397 0.2232242
## Honda-Alfa Romeo           3826.546378   1997.642271   5655.450484 0.0000000
## Hyundai-Alfa Romeo         5237.640298   3463.446469   7011.834126 0.0000000
## Infiniti-Alfa Romeo       11106.054842   8646.769534  13565.340149 0.0000000
## Iveco-Alfa Romeo           7363.767026   4792.874695   9934.659356 0.0000000
## Jaguar-Alfa Romeo         15124.449903  11515.324449  18733.575358 0.0000000
## Jeep-Alfa Romeo            8223.939343   5432.512987  11015.365698 0.0000000
## Kia-Alfa Romeo             5467.545430   3662.571791   7272.519068 0.0000000
## LADA-Alfa Romeo            4910.131273   2376.378925   7443.883621 0.0000000
## Lancia-Alfa Romeo           212.958273  -2724.657016   3150.573562 1.0000000
## Land Rover-Alfa Romeo     12506.750284  10131.372411  14882.128157 0.0000000
## Lexus-Alfa Romeo          14442.010748  12153.841826  16730.179671 0.0000000
## Lifan-Alfa Romeo           5591.986074   1803.888398   9380.083750 0.0000037
## Lincoln-Alfa Romeo         7048.922126   2815.367910  11282.476341 0.0000000
## Mazda-Alfa Romeo           2042.977004    291.080719   3794.873290 0.0031196
## Mercedes-Benz-Alfa Romeo   6701.266975   4998.046583   8404.487367 0.0000000
## Mini-Alfa Romeo           10445.150786   7168.236136  13722.065436 0.0000000
## Mitsubishi-Alfa Romeo      2730.912093    921.045935   4540.778251 0.0000016
## Moskvitch-Alfa Romeo      -1709.637915  -5266.135681   1846.859852 0.9998248
## Nissan-Alfa Romeo          3722.964077   1973.934289   5471.993864 0.0000000
## Opel-Alfa Romeo            1737.442803     47.924261   3426.961345 0.0327288
## Peugeot-Alfa Romeo         1693.667630    -21.901042   3409.236302 0.0600571
## Pontiac-Alfa Romeo         1674.993951  -2292.609577   5642.597479 0.9999961
## Porsche-Alfa Romeo        15941.273674  12525.762434  19356.784914 0.0000000
## Renault-Alfa Romeo         1870.673575    174.850023   3566.497128 0.0096789
## Rover-Alfa Romeo           -954.307884  -3189.065587   1280.449819 0.9999944
## Saab-Alfa Romeo            1442.035274  -1340.858560   4224.929108 0.9988450
## Seat-Alfa Romeo            1179.465250   -934.593310   3293.523810 0.9941623
## Skoda-Alfa Romeo          11037.523366   9255.598933  12819.447799 0.0000000
## SsangYong-Alfa Romeo       5030.772308   1930.336741   8131.207876 0.0000001
## Subaru-Alfa Romeo          4833.544508   2701.867425   6965.221591 0.0000000
## Suzuki-Alfa Romeo          2614.048664    377.055765   4851.041563 0.0029825
## Toyota-Alfa Romeo          7109.602359   5349.949395   8869.255323 0.0000000
## UAZ-Alfa Romeo              754.573687  -2420.768544   3929.915919 1.0000000
## Volkswagen-Alfa Romeo      3739.210724   2070.421478   5407.999970 0.0000000
## Volvo-Alfa Romeo           5727.791443   3879.120585   7576.462301 0.0000000
## ZAZ-Alfa Romeo            -1328.338906  -5295.942434   2639.264622 1.0000000
## AvtoVAZ-Audi              -5636.023634  -6804.528923  -4467.518345 0.0000000
## BMW-Audi                   2397.167626   1738.854709   3055.480543 0.0000000
## Buick-Audi                 5721.374226   2269.254097   9173.494355 0.0000000
## Cadillac-Audi              3938.179728    331.936932   7544.422525 0.0116938
## Chery-Audi                -2608.966820  -5723.324654    505.391015 0.3467819
## Chevrolet-Audi             1718.187072    500.261089   2936.113056 0.0000178
## Chrysler-Audi             -2159.453143  -3409.767738   -909.138547 0.0000000
## Citroen-Audi              -2719.619407  -3477.783159  -1961.455656 0.0000000
## Dacia-Audi                -1812.193398  -4900.656730   1276.269935 0.9846435
## Daewoo-Audi               -5578.336190  -7224.469862  -3932.202518 0.0000000
## Dodge-Audi                -1546.932970  -2986.842406   -107.023535 0.0157332
## Fiat-Audi                 -4144.924644  -5088.186216  -3201.663072 0.0000000
## Ford-Audi                 -2157.267600  -2818.446050  -1496.089150 0.0000000
## GAZ-Audi                  -3265.213023  -4988.841851  -1541.584195 0.0000000
## Geely-Audi                  614.287612  -2207.783873   3436.359097 1.0000000
## Great Wall-Audi            -731.184645  -4666.973090   3204.603800 1.0000000
## Honda-Audi                 -639.848449  -1595.013155    315.316257 0.8863305
## Hyundai-Audi                771.245471    -74.457269   1616.948211 0.1598496
## Infiniti-Audi              6639.660015   4738.204360   8541.115670 0.0000000
## Iveco-Audi                 2897.372199    853.616647   4941.127752 0.0000151
## Jaguar-Audi               10658.055077   7403.329907  13912.780247 0.0000000
## Jeep-Audi                  3757.544516   1442.482858   6072.606174 0.0000001
## Kia-Audi                   1001.150603     92.646767   1909.654439 0.0098688
## LADA-Audi                   443.736447  -1553.098635   2440.571529 1.0000000
## Lancia-Audi               -4253.436553  -6742.820608  -1764.052499 0.0000000
## Land Rover-Audi            8040.355457   6248.744612   9831.966303 0.0000000
## Lexus-Audi                 9975.615922   8301.349992  11649.881852 0.0000000
## Lifan-Audi                 1125.591247  -2326.528882   4577.711376 1.0000000
## Lincoln-Audi               2582.527299  -1353.261146   6518.315744 0.9124986
## Mazda-Audi                -2423.417822  -3221.283712  -1625.551932 0.0000000
## Mercedes-Benz-Audi         2234.872149   1550.467964   2919.276334 0.0000000
## Mini-Audi                  5978.755959   3096.808873   8860.703045 0.0000000
## Mitsubishi-Audi           -1735.482733  -2653.668387   -817.297080 0.0000000
## Moskvitch-Audi            -6176.032741  -9372.300212  -2979.765270 0.0000000
## Nissan-Audi                -743.430750  -1534.982758     48.121259 0.1145293
## Opel-Audi                 -2728.952023  -3378.507478  -2079.396569 0.0000000
## Peugeot-Audi              -2772.727196  -3487.307668  -2058.146725 0.0000000
## Pontiac-Audi              -2791.400875  -6439.595927    856.794177 0.5994716
## Porsche-Audi              11474.878847   8436.266267  14513.491428 0.0000000
## Renault-Audi              -2595.721251  -3261.504178  -1929.938325 0.0000000
## Rover-Audi                -5420.702710  -7021.199938  -3820.205483 0.0000000
## Saab-Audi                 -3024.359553  -5329.125804   -719.593301 0.0001637
## Seat-Audi                 -3286.929576  -4714.057104  -1859.802049 0.0000000
## Skoda-Audi                 6571.128540   5709.325738   7432.931341 0.0000000
## SsangYong-Audi              564.377482  -2115.202726   3243.957690 1.0000000
## Subaru-Audi                 367.149682  -1085.949272   1820.248636 1.0000000
## Suzuki-Audi               -1852.346162  -3455.962891   -248.729434 0.0038289
## Toyota-Audi                2643.207533   1828.451166   3457.963900 0.0000000
## UAZ-Audi                  -3711.821139  -6477.729249   -945.913029 0.0000853
## Volkswagen-Audi            -727.184102  -1320.738592   -133.629613 0.0009995
## Volvo-Audi                 1261.396617    268.908166   2253.885067 0.0003931
## ZAZ-Audi                  -5794.733733  -9442.928785  -2146.538680 0.0000002
## BMW-AvtoVAZ                8033.191260   6869.847475   9196.535045 0.0000000
## Buick-AvtoVAZ             11357.397860   7774.504301  14940.291419 0.0000000
## Cadillac-AvtoVAZ           9574.203362   5842.584414  13305.822310 0.0000000
## Chery-AvtoVAZ              3027.056814   -231.657286   6285.770914 0.1302828
## Chevrolet-AvtoVAZ          7354.210706   5803.940870   8904.480543 0.0000000
## Chrysler-AvtoVAZ           3476.570491   1900.728033   5052.412950 0.0000000
## Citroen-AvtoVAZ            2916.404227   1693.781987   4139.026466 0.0000000
## Dacia-AvtoVAZ              3823.830236    589.854568   7057.805905 0.0022971
## Daewoo-AvtoVAZ               57.687444  -1847.502555   1962.877443 1.0000000
## Dodge-AvtoVAZ              4089.090664   2358.965799   5819.215529 0.0000000
## Fiat-AvtoVAZ               1491.098990    145.834979   2836.363001 0.0088312
## Ford-AvtoVAZ               3478.756034   2313.788306   4643.723763 0.0000000
## GAZ-AvtoVAZ                2370.810611    398.276909   4343.344313 0.0015784
## Geely-AvtoVAZ              6250.311246   3269.693805   9230.928688 0.0000000
## Great Wall-AvtoVAZ         4904.838989    853.860891   8955.817086 0.0013274
## Honda-AvtoVAZ              4996.175185   3642.538424   6349.811947 0.0000000
## Hyundai-AvtoVAZ            6407.269105   5128.517374   7686.020837 0.0000000
## Infiniti-AvtoVAZ          12275.683649  10146.006098  14405.361201 0.0000000
## Iveco-AvtoVAZ              8533.395833   6275.757770  10791.033896 0.0000000
## Jaguar-AvtoVAZ            16294.078711  12900.963800  19687.193622 0.0000000
## Jeep-AvtoVAZ               9393.568150   6887.674428  11899.461873 0.0000000
## Kia-AvtoVAZ                6637.174237   5316.048927   7958.299548 0.0000000
## LADA-AvtoVAZ               6079.760081   3864.507677   8295.012485 0.0000000
## Lancia-AvtoVAZ             1382.587081  -1285.188367   4050.362528 0.9988410
## Land Rover-AvtoVAZ        13676.379091  11644.172830  15708.585353 0.0000000
## Lexus-AvtoVAZ             15611.639556  13682.090575  17541.188537 0.0000000
## Lifan-AvtoVAZ              6761.614881   3178.721323  10344.508440 0.0000000
## Lincoln-AvtoVAZ            8218.550933   4167.572836  12269.529031 0.0000000
## Mazda-AvtoVAZ              3212.605812   1964.974919   4460.236705 0.0000000
## Mercedes-Benz-AvtoVAZ      7870.895783   6692.591088   9049.200478 0.0000000
## Mini-AvtoVAZ              11614.779593   8577.410358  14652.148829 0.0000000
## Mitsubishi-AvtoVAZ         3900.540901   2572.739048   5228.342753 0.0000000
## Moskvitch-AvtoVAZ          -540.009107  -3877.091458   2797.073243 1.0000000
## Nissan-AvtoVAZ             4892.592884   3648.990276   6136.195493 0.0000000
## Opel-AvtoVAZ               2907.071611   1748.660995   4065.482226 0.0000000
## Peugeot-AvtoVAZ            2863.296438   1667.211944   4059.380932 0.0000000
## Pontiac-AvtoVAZ            2844.622759   -927.554332   6616.799849 0.6390892
## Porsche-AvtoVAZ           17110.902482  13924.500234  20297.304729 0.0000000
## Renault-AvtoVAZ            3040.302383   1872.715225   4207.889540 0.0000000
## Rover-AvtoVAZ               215.320924  -1650.579460   2081.221307 1.0000000
## Saab-AvtoVAZ               2611.664081    115.278626   5108.049537 0.0248018
## Seat-AvtoVAZ               2349.094058    629.592431   4068.595684 0.0000497
## Skoda-AvtoVAZ             12207.152174  10917.696112  13496.608235 0.0000000
## SsangYong-AvtoVAZ          6200.401116   3354.326107   9046.476125 0.0000000
## Subaru-AvtoVAZ             6003.173316   4262.056020   7744.290611 0.0000000
## Suzuki-AvtoVAZ             3783.677472   1915.100613   5652.254331 0.0000000
## Toyota-AvtoVAZ             8279.231167   7020.731742   9537.730592 0.0000000
## UAZ-AvtoVAZ                1924.202495  -1003.294822   4851.699811 0.9105272
## Volkswagen-AvtoVAZ         4908.839532   3780.876856   6036.802207 0.0000000
## Volvo-AvtoVAZ              6897.420251   5517.193389   8277.647113 0.0000000
## ZAZ-AvtoVAZ                -158.710099  -3930.887189   3613.466992 1.0000000
## Buick-BMW                  3324.206600   -126.169834   6774.583034 0.0834380
## Cadillac-BMW               1541.012102  -2063.561556   5145.585761 0.9999941
## Chery-BMW                 -5006.134445  -8118.559364  -1893.709527 0.0000001
## Chevrolet-BMW              -678.980553  -1891.955348    533.994241 0.9937579
## Chrysler-BMW              -4556.620768  -5802.112936  -3311.128601 0.0000000
## Citroen-BMW               -5116.787033  -5866.971295  -4366.602772 0.0000000
## Dacia-BMW                 -4209.361023  -7295.875224  -1122.846823 0.0000524
## Daewoo-BMW                -7975.503816  -9617.977627  -6333.030005 0.0000000
## Dodge-BMW                 -3944.100596  -5379.824572  -2508.376620 0.0000000
## Fiat-BMW                  -6542.092270  -7478.952209  -5605.232331 0.0000000
## Ford-BMW                  -4554.435225  -5206.448335  -3902.422116 0.0000000
## GAZ-BMW                   -5662.380649  -7382.514507  -3942.246791 0.0000000
## Geely-BMW                 -1782.880014  -4602.818243   1037.058216 0.9477997
## Great Wall-BMW            -3128.352271  -7062.611392    805.906850 0.4908723
## Honda-BMW                 -3037.016075  -3985.859458  -2088.172691 0.0000000
## Hyundai-BMW               -1625.922155  -2464.478817   -787.365492 0.0000000
## Infiniti-BMW               4242.492389   2344.204276   6140.780502 0.0000000
## Iveco-BMW                   500.204573  -1540.604313   2541.013460 1.0000000
## Jaguar-BMW                 8260.887451   5008.011787  11513.763115 0.0000000
## Jeep-BMW                   1360.376890   -952.083841   3672.837622 0.9839119
## Kia-BMW                   -1396.017023  -2297.872539   -494.161506 0.0000006
## LADA-BMW                  -1953.431179  -3947.250252     40.387894 0.0667270
## Lancia-BMW                -6650.604179  -9137.569624  -4163.638735 0.0000000
## Land Rover-BMW             5643.187832   3854.939087   7431.436577 0.0000000
## Lexus-BMW                  7578.448296   5907.780599   9249.115994 0.0000000
## Lifan-BMW                 -1271.576379  -4721.952813   2178.800056 1.0000000
## Lincoln-BMW                 185.359673  -3748.899448   4119.618795 1.0000000
## Mazda-BMW                 -4820.585448  -5610.872820  -4030.298076 0.0000000
## Mercedes-Benz-BMW          -162.295477   -837.849501    513.258547 1.0000000
## Mini-BMW                   3581.588333    701.730150   6461.446517 0.0006887
## Mitsubishi-BMW            -4132.650359  -5044.258304  -3221.042414 0.0000000
## Moskvitch-BMW             -8573.200367 -11767.584486  -5378.816248 0.0000000
## Nissan-BMW                -3140.598375  -3924.510828  -2356.685923 0.0000000
## Opel-BMW                  -5126.119649  -5766.343392  -4485.895907 0.0000000
## Peugeot-BMW               -5169.894822  -5876.003456  -4463.786189 0.0000000
## Pontiac-BMW               -5188.568501  -8835.113618  -1542.023384 0.0000134
## Porsche-BMW                9077.711222   6041.079771  12114.342672 0.0000000
## Renault-BMW               -4992.888877  -5649.570731  -4336.207024 0.0000000
## Rover-BMW                 -7817.870336  -9414.603102  -6221.137570 0.0000000
## Saab-BMW                  -5421.527178  -7723.680872  -3119.373485 0.0000000
## Seat-BMW                  -5684.097202  -7107.001672  -4261.192732 0.0000000
## Skoda-BMW                  4173.960914   3319.169582   5028.752245 0.0000000
## SsangYong-BMW             -1832.790144  -4510.123564    844.543276 0.8534099
## Subaru-BMW                -2030.017944  -3478.969538   -581.066350 0.0000223
## Suzuki-BMW                -4249.513788  -5849.373396  -2649.654181 0.0000000
## Toyota-BMW                  246.039907   -561.296509   1053.376323 1.0000000
## UAZ-BMW                   -6108.988765  -8872.720269  -3345.257262 0.0000000
## Volkswagen-BMW            -3124.351728  -3707.679324  -2541.024133 0.0000000
## Volvo-BMW                 -1135.771009  -2122.177354   -149.364665 0.0040970
## ZAZ-BMW                   -8191.901358 -11838.446475  -4545.356241 0.0000000
## Cadillac-Buick            -1783.194498  -6730.588635   3164.199640 1.0000000
## Chery-Buick               -8330.341045 -12931.530713  -3729.151377 0.0000000
## Chevrolet-Buick           -4003.187154  -7602.501719   -403.872588 0.0082659
## Chrysler-Buick            -7880.827368 -11491.230148  -4270.424589 0.0000000
## Citroen-Buick             -8440.993633 -11911.805342  -4970.181925 0.0000000
## Dacia-Buick               -7533.567624 -12117.269991  -2949.865256 0.0000000
## Daewoo-Buick             -11299.710416 -15065.540697  -7533.880134 0.0000000
## Dodge-Buick               -7268.307196 -10948.668703  -3587.945689 0.0000000
## Fiat-Buick                -9866.298870 -13382.186245  -6350.411495 0.0000000
## Ford-Buick                -7878.641825 -11329.566134  -4427.717517 0.0000000
## GAZ-Buick                 -8986.587249 -12786.931704  -5186.242794 0.0000000
## Geely-Buick               -5107.086614  -9515.692868   -698.480359 0.0036005
## Great Wall-Buick          -6452.558871 -11645.068122  -1260.049620 0.0007028
## Honda-Buick               -6361.222675  -9880.322170  -2842.123180 0.0000000
## Hyundai-Buick             -4950.128755  -8441.107810  -1459.149699 0.0000150
## Infiniti-Buick              918.285789  -2965.945827   4802.517406 1.0000000
## Iveco-Buick               -2824.002027  -6779.840547   1131.836494 0.7731917
## Jaguar-Buick               4936.680851    239.345695   9634.016008 0.0229918
## Jeep-Buick                -1963.829710  -6066.418176   2138.758756 0.9998435
## Kia-Buick                 -4720.223623  -8226.945862  -1213.501384 0.0000780
## LADA-Buick                -5277.637779  -9209.440417  -1345.835141 0.0000848
## Lancia-Buick              -9974.810779 -14178.232554  -5771.389005 0.0000000
## Land Rover-Buick           2318.981232  -1512.675207   6150.637670 0.9737066
## Lexus-Buick                4254.241696    476.029415   8032.453978 0.0064846
## Lifan-Buick               -4595.782979  -9431.985521    240.419563 0.0993122
## Lincoln-Buick             -3138.846927  -8331.356178   2053.662324 0.9742250
## Mazda-Buick               -8144.792048 -11624.491980  -4665.092116 0.0000000
## Mercedes-Benz-Buick       -3486.502077  -6941.951502    -31.052652 0.0438249
## Mini-Buick                  257.381733  -4189.790475   4704.553941 1.0000000
## Mitsubishi-Buick          -7456.856959 -10966.099974  -3947.613945 0.0000000
## Moskvitch-Buick          -11897.406967 -16554.428267  -7240.385667 0.0000000
## Nissan-Buick              -6464.804976  -9943.062617  -2986.547334 0.0000000
## Opel-Buick                -8450.326249 -11899.042522  -5001.609977 0.0000000
## Peugeot-Buick             -8494.101422 -11955.654093  -5032.548752 0.0000000
## Pontiac-Buick             -8512.775101 -13490.831828  -3534.718374 0.0000000
## Porsche-Buick              5753.504622   1203.242205  10303.767038 0.0004500
## Renault-Buick             -8317.095477 -11768.904937  -4865.286017 0.0000000
## Rover-Buick              -11142.076936 -14888.183317  -7395.970555 0.0000000
## Saab-Buick                -8745.733779 -12842.521437  -4648.946120 0.0000000
## Seat-Buick                -9008.303802 -12683.683323  -5332.924282 0.0000000
## Skoda-Buick                 849.754314  -2645.159950   4344.668577 1.0000000
## SsangYong-Buick           -5156.996744  -9475.778022   -838.215465 0.0018364
## Subaru-Buick              -5354.224544  -9039.766324  -1668.682764 0.0000066
## Suzuki-Buick              -7573.720388 -11321.160615  -3826.280161 0.0000000
## Toyota-Buick              -3078.166693  -6561.778264    405.444878 0.2200643
## UAZ-Buick                 -9433.195365 -13806.062767  -5060.327963 0.0000000
## Volkswagen-Buick          -6448.558328  -9887.166851  -3009.949806 0.0000000
## Volvo-Buick               -4459.977609  -7989.390445   -930.564774 0.0004573
## ZAZ-Buick                -11516.107958 -16494.164686  -6538.051231 0.0000000
## Chery-Cadillac            -6547.146548 -11265.069828  -1829.223267 0.0000304
## Chevrolet-Cadillac        -2219.992656  -5967.380955   1527.395643 0.9817803
## Chrysler-Cadillac         -6097.632871  -9855.672513  -2339.593229 0.0000001
## Citroen-Cadillac          -6657.799135 -10281.938708  -3033.659563 0.0000000
## Dacia-Cadillac            -5750.373126 -10451.243377  -1049.502874 0.0010376
## Daewoo-Cadillac           -9516.515918 -13424.115108  -5608.916728 0.0000000
## Dodge-Cadillac            -5485.112698  -9310.411974  -1659.813423 0.0000103
## Fiat-Cadillac             -8083.104372 -11750.435521  -4415.773223 0.0000000
## Ford-Cadillac             -6095.447328  -9700.545427  -2490.349228 0.0000000
## GAZ-Cadillac              -7203.392751 -11144.264698  -3262.520804 0.0000000
## Geely-Cadillac            -3323.892116  -7854.197054   1206.412822 0.7097684
## Great Wall-Cadillac       -4669.364373  -9965.590015    626.861268 0.2247768
## Honda-Cadillac            -4578.028177  -8248.438914   -907.617440 0.0006400
## Hyundai-Cadillac          -3166.934257  -6810.392571    476.524057 0.2560161
## Infiniti-Cadillac          2701.480287  -1320.348771   6723.309345 0.8825204
## Iveco-Cadillac            -1040.807529  -5131.835776   3050.220719 1.0000000
## Jaguar-Cadillac            6719.875349   1908.138522  11531.612176 0.0000248
## Jeep-Cadillac              -180.635212  -4413.729334   4052.458910 1.0000000
## Kia-Cadillac              -2937.029125  -6595.574544    721.516294 0.4637593
## LADA-Cadillac             -3494.443281  -7562.234538    573.347976 0.2835284
## Lancia-Cadillac           -8191.616282 -12522.506298  -3860.726265 0.0000000
## Land Rover-Cadillac        4102.175729    131.099706   8073.251753 0.0304689
## Lexus-Cadillac             6037.436194   2117.902833   9956.969555 0.0000007
## Lifan-Cadillac            -2812.588481  -7759.982618   2134.805656 0.9915164
## Lincoln-Cadillac          -1355.652429  -6651.878070   3940.573213 1.0000000
## Mazda-Cadillac            -6361.597550  -9994.250209  -2728.944891 0.0000000
## Mercedes-Benz-Cadillac    -1703.307579  -5312.737514   1906.122355 0.9998937
## Mini-Cadillac              2040.576231  -2527.267283   6608.419745 0.9999777
## Mitsubishi-Cadillac       -5673.662462  -9334.624119  -2012.700804 0.0000006
## Moskvitch-Cadillac       -10114.212469 -14886.601924  -5341.823014 0.0000000
## Nissan-Cadillac           -4681.610478  -8312.881597  -1050.339358 0.0002677
## Opel-Cadillac             -6667.131752 -10270.116299  -3064.147204 0.0000000
## Peugeot-Cadillac          -6710.906925 -10326.180167  -3095.633683 0.0000000
## Pontiac-Cadillac          -6729.580604 -11815.728704  -1643.432503 0.0001292
## Porsche-Cadillac           7536.699119   2868.429442  12204.968797 0.0000001
## Renault-Cadillac          -6533.900979 -10139.846385  -2927.955574 0.0000000
## Rover-Cadillac            -9358.882438 -13247.476881  -5470.287996 0.0000000
## Saab-Cadillac             -6962.539281 -11190.011674  -2735.066887 0.0000000
## Seat-Cadillac             -7225.109305 -11045.615599  -3404.603011 0.0000000
## Skoda-Cadillac             2632.948811  -1014.280196   6280.177819 0.7482850
## SsangYong-Cadillac        -3373.802246  -7816.743328   1069.138835 0.6203061
## Subaru-Cadillac           -3571.030046  -7401.313578    259.253485 0.1248968
## Suzuki-Cadillac           -5790.525890  -9680.405320  -1900.646461 0.0000027
## Toyota-Cadillac           -1294.972195  -4931.371967   2341.427577 1.0000000
## UAZ-Cadillac              -7650.000867 -12145.534544  -3154.467191 0.0000000
## Volkswagen-Cadillac       -4665.363831  -8258.674601  -1072.053060 0.0002206
## Volvo-Cadillac            -2676.783112  -6357.083193   1003.516970 0.7308371
## ZAZ-Cadillac              -9732.913461 -14819.061561  -4646.765360 0.0000000
## Chevrolet-Chery            4327.153892   1050.393804   7603.913980 0.0001366
## Chrysler-Chery              449.513677  -2839.422255   3738.449609 1.0000000
## Citroen-Chery              -110.652588  -3245.716423   3024.411247 1.0000000
## Dacia-Chery                 796.773422  -3538.248923   5131.795767 1.0000000
## Daewoo-Chery              -2969.369370  -6428.208633    489.469892 0.2851084
## Dodge-Chery                1062.033849  -2303.549630   4427.617329 1.0000000
## Fiat-Chery                -1535.957824  -4720.852700   1648.937051 0.9998090
## Ford-Chery                  451.699220  -2661.333051   3564.731491 1.0000000
## GAZ-Chery                  -656.246203  -4152.631381   2840.138975 1.0000000
## Geely-Chery                3223.254432   -926.191367   7372.700231 0.5572329
## Great Wall-Chery           1877.782174  -3096.576443   6852.140792 0.9999999
## Honda-Chery                1969.118371  -1219.322093   5157.558834 0.9634981
## Hyundai-Chery              3380.212291    222.835833   6537.588749 0.0167363
## Infiniti-Chery             9248.626835   5661.239682  12836.013987 0.0000000
## Iveco-Chery                5506.339019   1841.540289   9171.137749 0.0000019
## Jaguar-Chery              13267.021897   8812.019213  17722.024580 0.0000000
## Jeep-Chery                 6366.511336   2543.773645  10189.249027 0.0000000
## Kia-Chery                  3610.117423    435.343069   6784.891776 0.0053133
## LADA-Chery                 3052.703266   -586.137665   6691.544197 0.3430383
## Lancia-Chery              -1644.469734  -5575.226143   2286.286675 0.9999970
## Land Rover-Chery          10649.322277   7118.928192  14179.716362 0.0000000
## Lexus-Chery               12584.582742   9112.266601  16056.898882 0.0000000
## Lifan-Chery                3734.558067   -866.631601   8335.747735 0.4328201
## Lincoln-Chery              5191.494119    217.135501  10165.852736 0.0258104
## Mazda-Chery                 185.548997  -2959.352106   3330.450101 1.0000000
## Mercedes-Benz-Chery        4843.838969   1725.791172   7961.886765 0.0000005
## Mini-Chery                 8587.722779   4397.325187  12778.120371 0.0000000
## Mitsubishi-Chery            873.484086  -2304.074390   4051.042562 1.0000000
## Moskvitch-Chery           -3567.065922  -7979.541273    845.409429 0.4440685
## Nissan-Chery               1865.536070  -1277.769126   5008.841266 0.9811846
## Opel-Chery                 -119.985204  -3230.569596   2990.599189 1.0000000
## Peugeot-Chery              -163.760377  -3288.570487   2961.049733 1.0000000
## Pontiac-Chery              -182.434056  -4932.501436   4567.633324 1.0000000
## Porsche-Chery             14083.845667   9784.196915  18383.494419 0.0000000
## Renault-Chery                13.245568  -3100.767900   3127.259036 1.0000000
## Rover-Chery               -2811.735891  -6249.090157    625.618375 0.4111389
## Saab-Chery                 -415.392733  -4231.904288   3401.118822 1.0000000
## Seat-Chery                 -677.962757  -4038.097569   2682.172055 1.0000000
## Skoda-Chery                9180.095359   6018.368451  12341.822268 0.0000000
## SsangYong-Chery            3173.344302   -880.538166   7227.226770 0.5354533
## Subaru-Chery               2976.116501   -395.130975   6347.363978 0.2220134
## Suzuki-Chery                756.620657  -2682.187216   4195.428530 1.0000000
## Toyota-Chery               5252.174352   2102.945731   8401.402974 0.0000000
## UAZ-Chery                 -1102.854320  -5214.309129   3008.600489 1.0000000
## Volkswagen-Chery           1881.782717  -1217.591398   4981.156832 0.9722772
## Volvo-Chery                3870.363436    670.543707   7070.183165 0.0013596
## ZAZ-Chery                 -3185.766913  -7935.834293   1564.300467 0.8846764
## Chrysler-Chevrolet        -3877.640215  -5490.469575  -2264.810855 0.0000000
## Citroen-Chevrolet         -4437.806480  -5707.745151  -3167.867808 0.0000000
## Dacia-Chevrolet           -3530.380470  -6782.539401   -278.221539 0.0130492
## Daewoo-Chevrolet          -7296.523262  -9232.417894  -5360.628631 0.0000000
## Dodge-Chevrolet           -3265.120043  -5028.999613  -1501.240472 0.0000000
## Fiat-Chevrolet            -5863.111716  -7251.518843  -4474.704590 0.0000000
## Ford-Chevrolet            -3875.454672  -5089.987051  -2660.922293 0.0000000
## GAZ-Chevrolet             -4983.400095  -6985.605952  -2981.194238 0.0000000
## Geely-Chevrolet           -1103.899460  -4104.236012   1896.437091 1.0000000
## Great Wall-Chevrolet      -2449.371718  -6514.880620   1616.137185 0.9756340
## Honda-Chevrolet           -2358.035521  -3754.556760   -961.514282 0.0000000
## Hyundai-Chevrolet          -946.941601  -2271.005452    377.122249 0.7692445
## Infiniti-Chevrolet         4921.472943   2764.283669   7078.662217 0.0000000
## Iveco-Chevrolet            1179.185127  -1104.423577   3462.793831 0.9989366
## Jaguar-Chevrolet           8939.868005   5529.418197  12350.317812 0.0000000
## Jeep-Chevrolet             2039.357444   -489.959151   4568.674039 0.4514558
## Kia-Chevrolet              -717.036469  -2082.068035    647.995097 0.9984146
## LADA-Chevrolet            -1274.450626  -3516.164769    967.263518 0.9915114
## Lancia-Chevrolet          -5971.623626  -8661.412638  -3281.834614 0.0000000
## Land Rover-Chevrolet       6322.168385   4261.148885   8383.187885 0.0000000
## Lexus-Chevrolet            8257.428850   6297.556823  10217.300876 0.0000000
## Lifan-Chevrolet            -592.595825  -4191.910391   3006.718740 1.0000000
## Lincoln-Chevrolet           864.340227  -3201.168676   4929.849130 1.0000000
## Mazda-Chevrolet           -4141.604895  -5435.638099  -2847.571690 0.0000000
## Mercedes-Benz-Chevrolet     516.685077   -710.645785   1744.015938 0.9999964
## Mini-Chevrolet             4260.568887   1203.846629   7317.291145 0.0000264
## Mitsubishi-Chevrolet      -3453.669806  -4825.164191  -2082.175420 0.0000000
## Moskvitch-Chevrolet       -7894.219814 -11248.926612  -4539.513015 0.0000000
## Nissan-Chevrolet          -2461.617822  -3751.767634  -1171.468010 0.0000000
## Opel-Chevrolet            -4447.139096  -5655.383378  -3238.894814 0.0000000
## Peugeot-Chevrolet         -4490.914269  -5735.324654  -3246.503884 0.0000000
## Pontiac-Chevrolet         -4509.587948  -8297.365541   -721.810355 0.0019651
## Porsche-Chevrolet          9756.691775   6551.836338  12961.547212 0.0000000
## Renault-Chevrolet         -4313.908324  -5530.953459  -3096.863189 0.0000000
## Rover-Chevrolet           -7138.889783  -9036.130761  -5241.648804 0.0000000
## Saab-Chevrolet            -4742.546625  -7262.443336  -2222.649915 0.0000000
## Seat-Chevrolet            -5005.116649  -6758.577494  -3251.655804 0.0000000
## Skoda-Chevrolet            4852.941467   3518.536722   6187.346213 0.0000000
## SsangYong-Chevrolet       -1153.809590  -4020.529326   1712.910146 0.9999992
## Subaru-Chevrolet          -1351.037391  -3125.700324    423.625543 0.6133698
## Suzuki-Chevrolet          -3570.533235  -5470.406538  -1670.659932 0.0000000
## Toyota-Chevrolet            925.020460   -379.494734   2229.535655 0.7875086
## UAZ-Chevrolet             -5430.008212  -8377.580031  -2482.436393 0.0000000
## Volkswagen-Chevrolet      -2445.371175  -3624.455094  -1266.287256 0.0000000
## Volvo-Chevrolet            -456.790456  -1879.100296    965.519384 1.0000000
## ZAZ-Chevrolet             -7512.920805 -11300.698398  -3725.143212 0.0000000
## Citroen-Chrysler           -560.166265  -1861.199361    740.866831 0.9999927
## Dacia-Chrysler              347.259745  -2917.166790   3611.686279 1.0000000
## Daewoo-Chrysler           -3418.883047  -5375.316259  -1462.449836 0.0000000
## Dodge-Chrysler              612.520172  -1173.876767   2398.917112 1.0000000
## Fiat-Chrysler             -1985.471501  -3402.375604   -568.567399 0.0000222
## Ford-Chrysler                 2.185543  -1244.823593   1249.194679 1.0000000
## GAZ-Chrysler              -1105.759880  -3127.830893    916.311132 0.9961485
## Geely-Chrysler             2773.740755   -239.888670   5787.370179 0.1445490
## Great Wall-Chrysler        1428.268497  -2647.060388   5503.597383 1.0000000
## Honda-Chrysler             1519.604694     94.748751   2944.460637 0.0178929
## Hyundai-Chrysler           2930.698614   1576.782824   4284.614404 0.0000000
## Infiniti-Chrysler          8799.113158   6623.473378  10974.752937 0.0000000
## Iveco-Chrysler             5056.825342   2755.779579   7357.871104 0.0000000
## Jaguar-Chrysler           12817.508220   9395.358197  16239.658242 0.0000000
## Jeep-Chrysler              5916.997659   3371.926869   8462.068448 0.0000000
## Kia-Chrysler               3160.603746   1766.597267   4554.610225 0.0000000
## LADA-Chrysler              2603.189589    343.715051   4862.664128 0.0040448
## Lancia-Chrysler           -2093.983411  -4798.592036    610.625214 0.5665455
## Land Rover-Chrysler       10199.808600   8119.485484  12280.131715 0.0000000
## Lexus-Chrysler            12135.069065  10154.907140  14115.230989 0.0000000
## Lifan-Chrysler             3285.044390   -325.358390   6895.447169 0.1637915
## Lincoln-Chrysler           4741.980442    666.651556   8817.309327 0.0032726
## Mazda-Chrysler             -263.964680  -1588.526804   1060.597445 1.0000000
## Mercedes-Benz-Chrysler     4394.325291   3134.847650   5653.802933 0.0000000
## Mini-Chrysler              8138.209102   5068.438125  11207.980079 0.0000000
## Mitsubishi-Chrysler         423.970409   -976.365171   1824.305989 1.0000000
## Moskvitch-Chrysler        -4016.579599  -7383.180346   -649.978852 0.0018728
## Nissan-Chrysler            1416.022393     95.253895   2736.790890 0.0163165
## Opel-Chrysler              -569.498881  -1810.384505    671.386743 0.9999512
## Peugeot-Chrysler           -613.274054  -1889.401043    662.852936 0.9998261
## Pontiac-Chrysler           -631.947733  -4430.263410   3166.367944 1.0000000
## Porsche-Chrysler          13634.331990  10417.028576  16851.635404 0.0000000
## Renault-Chrysler           -436.268109  -1685.724690    813.188472 1.0000000
## Rover-Chrysler            -3261.249568  -5179.443045  -1343.056090 0.0000000
## Saab-Chrysler              -864.906410  -3400.615841   1670.803021 1.0000000
## Seat-Chrysler             -1127.476434  -2903.586741    648.633873 0.9446190
## Skoda-Chrysler             8730.581682   7366.551290  10094.612074 0.0000000
## SsangYong-Chrysler         2723.830625   -156.798635   5604.459884 0.1055801
## Subaru-Chrysler            2526.602824    729.557635   4323.648014 0.0000199
## Suzuki-Chrysler             307.106980  -1613.690108   2227.904069 1.0000000
## Toyota-Chrysler            4802.660675   3467.856278   6137.465073 0.0000000
## UAZ-Chrysler              -1552.367997  -4513.469568   1408.733574 0.9984849
## Volkswagen-Chrysler        1432.269040    219.758515   2644.779566 0.0023479
## Volvo-Chrysler             3420.849759   1970.709019   4870.990500 0.0000000
## ZAZ-Chrysler              -3635.280590  -7433.596267    163.035087 0.0908300
## Dacia-Citroen               907.426010  -2201.915767   4016.767787 1.0000000
## Daewoo-Citroen            -2858.716783  -4543.696485  -1173.737080 0.0000000
## Dodge-Citroen              1172.686437   -311.476530   2656.849404 0.5089100
## Fiat-Citroen              -1425.305237  -2434.831325   -415.779148 0.0000174
## Ford-Citroen                562.351808   -190.348313   1315.051929 0.6637758
## GAZ-Citroen                -545.593616  -2306.359605   1215.172373 1.0000000
## Geely-Citroen              3333.907020    489.001398   6178.812641 0.0028018
## Great Wall-Citroen         1988.434762  -1963.758453   5940.627977 0.9994336
## Honda-Citroen              2079.770959   1059.114236   3100.427681 0.0000000
## Hyundai-Citroen            3490.864879   2571.836232   4409.893525 0.0000000
## Infiniti-Citroen           9359.279423   7424.096192  11294.462653 0.0000000
## Iveco-Citroen              5616.991607   3541.819978   7692.163235 0.0000000
## Jaguar-Citroen            13377.674484  10103.130782  16652.218187 0.0000000
## Jeep-Citroen               6477.163924   4134.321417   8820.006430 0.0000000
## Kia-Citroen                3720.770011   2743.641693   4697.898328 0.0000000
## LADA-Citroen               3163.355854   1134.378063   5192.333645 0.0000005
## Lancia-Citroen            -1533.817146  -4049.057393    981.423101 0.9702123
## Land Rover-Citroen        10759.974865   8932.607920  12587.341810 0.0000000
## Lexus-Citroen             12695.235329  10982.761408  14407.709251 0.0000000
## Lifan-Citroen              3845.210655    374.398946   7316.022363 0.0089136
## Lincoln-Citroen            5302.146707   1349.953491   9254.339922 0.0000861
## Mazda-Citroen               296.201585   -579.007252   1171.410422 1.0000000
## Mercedes-Benz-Citroen      4954.491556   4181.310066   5727.673047 0.0000000
## Mini-Citroen               8698.375367   5794.064857  11602.685876 0.0000000
## Mitsubishi-Citroen          984.136674     -1.999941   1970.273289 0.0514934
## Moskvitch-Citroen         -3456.413334  -6672.859552   -239.967115 0.0156606
## Nissan-Citroen             1976.188658   1106.731867   2845.645448 0.0000000
## Opel-Citroen                 -9.332616   -751.843773    733.178541 1.0000000
## Peugeot-Citroen             -53.107789   -853.123901    746.908323 1.0000000
## Pontiac-Citroen             -71.781468  -3737.668491   3594.105555 1.0000000
## Porsche-Citroen           14194.498255  11134.667059  17254.329450 0.0000000
## Renault-Citroen             123.898156   -632.849777    880.646089 1.0000000
## Rover-Citroen             -2701.083303  -4341.507609  -1060.658997 0.0000000
## Saab-Citroen               -304.740145  -2637.409862   2027.929571 1.0000000
## Seat-Citroen               -567.310169  -2039.075608    904.455270 0.9999998
## Skoda-Citroen              9290.747947   8356.882540  10224.613354 0.0000000
## SsangYong-Citroen          3283.996889    580.378829   5987.614950 0.0012298
## Subaru-Citroen             3086.769089   1589.806464   4583.731714 0.0000000
## Suzuki-Citroen              867.273245   -776.194778   2510.741268 0.9982393
## Toyota-Citroen             5362.826940   4472.193196   6253.460685 0.0000000
## UAZ-Citroen                -992.201732  -3781.403804   1797.000341 1.0000000
## Volkswagen-Citroen         1992.435305   1298.383822   2686.486788 0.0000000
## Volvo-Citroen              3981.016024   2925.348532   5036.683516 0.0000000
## ZAZ-Citroen               -3075.114325  -6741.001348    590.772698 0.3432748
## Daewoo-Dacia              -3766.142792  -7201.684974   -330.600611 0.0108902
## Dodge-Dacia                 265.260427  -3076.375877   3606.896732 1.0000000
## Fiat-Dacia                -2332.731246  -5492.309763    826.847271 0.6942152
## Ford-Dacia                 -345.074202  -3432.200852   2742.052448 1.0000000
## GAZ-Dacia                 -1453.019625  -4926.359567   2020.320316 0.9999971
## Geely-Dacia                2426.481010  -1703.565174   6556.527193 0.9842824
## Great Wall-Dacia           1081.008752  -3877.178890   6039.196394 1.0000000
## Honda-Dacia                1172.344949  -1990.807534   4335.497431 1.0000000
## Hyundai-Dacia              2583.438869   -548.398792   5715.276530 0.3880604
## Infiniti-Dacia             8451.853413   4886.923172  12016.783653 0.0000000
## Iveco-Dacia                4709.565597   1066.746528   8352.384666 0.0002481
## Jaguar-Dacia              12470.248475   8033.309221  16907.187729 0.0000000
## Jeep-Dacia                 5569.737914   1768.066638   9371.409190 0.0000049
## Kia-Dacia                  2813.344001   -336.032641   5962.720643 0.1979198
## LADA-Dacia                 2255.929844  -1360.773676   5872.633365 0.9573940
## Lancia-Dacia              -2441.243156  -6351.515139   1469.028827 0.9568022
## Land Rover-Dacia           9852.548855   6344.976556  13360.121154 0.0000000
## Lexus-Dacia               11787.809320   8338.699229  15236.919410 0.0000000
## Lifan-Dacia                2937.784645  -1645.917723   7521.487013 0.9364547
## Lincoln-Dacia              4394.720697   -563.466945   9352.908339 0.2136289
## Mazda-Dacia                -611.224425  -3730.484592   2508.035743 1.0000000
## Mercedes-Benz-Dacia        4047.065547    954.881351   7139.249742 0.0001763
## Mini-Dacia                 7790.949357   3619.760915  11962.137799 0.0000000
## Mitsubishi-Dacia             76.710664  -3075.472532   3228.893861 1.0000000
## Moskvitch-Dacia           -4363.839344  -8758.076451     30.397764 0.0552529
## Nissan-Dacia               1068.762648  -2048.888486   4186.413782 1.0000000
## Opel-Dacia                 -916.758626  -4001.416840   2167.899589 1.0000000
## Peugeot-Dacia              -960.533799  -4059.536745   2138.469148 1.0000000
## Pontiac-Dacia              -979.207478  -5712.337642   3753.922686 1.0000000
## Porsche-Dacia             13287.072245   9006.142390  17568.002101 0.0000000
## Renault-Dacia              -783.527854  -3871.643933   2304.588225 1.0000000
## Rover-Dacia               -3608.509313  -7022.419884   -194.598742 0.0208700
## Saab-Dacia                -1212.166155  -5007.576737   2583.244427 1.0000000
## Seat-Dacia                -1474.736179  -4810.884705   1861.412347 0.9999837
## Skoda-Dacia                8383.321937   5247.098399  11519.545475 0.0000000
## SsangYong-Dacia            2376.570880  -1657.452435   6410.594194 0.9834901
## Subaru-Dacia               2179.343079  -1167.997743   5526.683902 0.9210989
## Suzuki-Dacia                -40.152765  -3455.526920   3375.221391 1.0000000
## Toyota-Dacia               4455.400930   1331.777722   7579.024139 0.0000123
## UAZ-Dacia                 -1899.627742  -5991.502823   2192.247340 0.9999325
## Volkswagen-Dacia           1085.009295  -1988.344076   4158.362666 1.0000000
## Volvo-Dacia                3073.590014   -101.032379   6248.212407 0.0782541
## ZAZ-Dacia                 -3982.540335  -8715.670499    750.589829 0.3353173
## Dodge-Daewoo               4031.403220   1948.692605   6114.113835 0.0000000
## Fiat-Daewoo                1433.411546   -342.563317   3209.386410 0.4485735
## Ford-Daewoo                3421.068590   1777.444161   5064.693020 0.0000000
## GAZ-Daewoo                 2313.123167     25.058338   4601.187996 0.0425667
## Geely-Daewoo               6192.623802   2994.431846   9390.815758 0.0000000
## Great Wall-Daewoo          4847.151545    633.510007   9060.793082 0.0041786
## Honda-Daewoo               4938.487741   3156.162311   6720.813171 0.0000000
## Hyundai-Daewoo             6349.581661   4623.442198   8075.721125 0.0000000
## Infiniti-Daewoo           12217.996205   9793.150245  14642.842165 0.0000000
## Iveco-Daewoo               8475.708389   5937.740485  11013.676293 0.0000000
## Jaguar-Daewoo             16236.391267  12650.644447  19822.138087 0.0000000
## Jeep-Daewoo                9335.880706   6574.747822  12097.013590 0.0000000
## Kia-Daewoo                 6579.486793   4821.725847   8337.247739 0.0000000
## LADA-Daewoo                6022.072637   3521.733726   8522.411548 0.0000000
## Lancia-Daewoo              1324.899637  -1583.945030   4233.744303 0.9999608
## Land Rover-Daewoo         13618.691647  11278.987875  15958.395420 0.0000000
## Lexus-Daewoo              15553.952112  13302.838893  17805.065331 0.0000000
## Lifan-Daewoo               6703.927437   2938.097156  10469.757719 0.0000000
## Lincoln-Daewoo             8160.863489   3947.221952  12374.505026 0.0000000
## Mazda-Daewoo               3154.918368   1451.705433   4858.131303 0.0000000
## Mercedes-Benz-Daewoo       7813.208339   6160.104165   9466.312513 0.0000000
## Mini-Daewoo               11557.092149   8305.944148  14808.240151 0.0000000
## Mitsubishi-Daewoo          3842.853457   2080.068950   5605.637963 0.0000000
## Moskvitch-Daewoo           -597.696551  -4130.467428   2935.074326 1.0000000
## Nissan-Daewoo              4834.905440   3134.641077   6535.169803 0.0000000
## Opel-Daewoo                2849.384167   1210.400759   4488.367575 0.0000000
## Peugeot-Daewoo             2805.608994   1139.785001   4471.432986 0.0000000
## Pontiac-Daewoo             2786.935315  -1159.413816   6733.284445 0.7959176
## Porsche-Daewoo            17053.215037  13662.417087  20444.012988 0.0000000
## Renault-Daewoo             2982.614939   1337.132873   4628.097004 0.0000000
## Rover-Daewoo                157.633480  -2039.167763   2354.434722 1.0000000
## Saab-Daewoo                2553.976637   -198.529820   5306.483095 0.1319617
## Seat-Daewoo                2291.406613    217.512378   4365.300849 0.0093870
## Skoda-Daewoo              12149.464730  10415.380420  13883.549039 0.0000000
## SsangYong-Daewoo           6142.713672   3069.524057   9215.903287 0.0000000
## Subaru-Daewoo              5945.485872   3853.634803   8037.336940 0.0000000
## Suzuki-Daewoo              3725.990028   1526.915010   5925.065046 0.0000000
## Toyota-Daewoo              8221.543723   6510.353418   9932.734028 0.0000000
## UAZ-Daewoo                 1866.515051  -1282.229460   5015.259562 0.9815787
## Volkswagen-Daewoo          4851.152088   3233.545444   6468.758732 0.0000000
## Volvo-Daewoo               6839.732806   5037.129787   8642.335826 0.0000000
## ZAZ-Daewoo                 -216.397543  -4162.746673   3729.951588 1.0000000
## Fiat-Dodge                -2597.991674  -4184.708356  -1011.274991 0.0000001
## Ford-Dodge                 -610.334629  -2047.374775    826.705516 0.9999952
## GAZ-Dodge                 -1718.280053  -3862.766886    426.206780 0.4691695
## Geely-Dodge                2161.220582   -935.877237   5258.318402 0.8193913
## Great Wall-Dodge            815.748325  -3321.685435   4953.182085 1.0000000
## Honda-Dodge                 907.084521   -686.737003   2500.906046 0.9913327
## Hyundai-Dodge              2318.178441    787.446407   3848.910476 0.0000014
## Infiniti-Dodge             8186.592985   5896.732499  10476.453471 0.0000000
## Iveco-Dodge                4444.305169   2034.976592   6853.633747 0.0000000
## Jaguar-Dodge              12204.988047   8709.109993  15700.866101 0.0000000
## Jeep-Dodge                 5304.477486   2661.101252   7947.853721 0.0000000
## Kia-Dodge                  2548.083573    981.780072   4114.387075 0.0000001
## LADA-Dodge                 1990.669417   -378.988319   4360.327153 0.3394870
## Lancia-Dodge              -2706.503583  -5503.816653     90.809486 0.0789356
## Land Rover-Dodge           9587.288428   7387.789198  11786.787657 0.0000000
## Lexus-Dodge               11522.548892   9417.532540  13627.565244 0.0000000
## Lifan-Dodge                2672.524217  -1007.837290   6352.885725 0.7346379
## Lincoln-Dodge              4129.460269     -7.973491   8266.894030 0.0514182
## Mazda-Dodge                -876.484852  -2381.316210    628.346506 0.9865763
## Mercedes-Benz-Dodge        3781.805119   2333.932015   5229.678223 0.0000000
## Mini-Dodge                 7525.688930   4373.936013  10677.441846 0.0000000
## Mitsubishi-Dodge           -188.549763  -1760.488799   1383.389272 1.0000000
## Moskvitch-Dodge           -4629.099771  -8070.618794  -1187.580748 0.0000797
## Nissan-Dodge                803.502221   -697.991043   2304.995484 0.9975905
## Opel-Dodge                -1182.019053  -2613.748681    249.710574 0.3857758
## Peugeot-Dodge             -1225.794226  -2688.173346    236.584893 0.3452286
## Pontiac-Dodge             -1244.467905  -5109.342363   2620.406553 1.0000000
## Porsche-Dodge             13021.811818   9726.194447  16317.429188 0.0000000
## Renault-Dodge             -1048.788281  -2487.952741    390.376179 0.7261919
## Rover-Dodge               -3873.769740  -5920.601148  -1826.938332 0.0000000
## Saab-Dodge                -1477.426582  -4111.790816   1156.937651 0.9935149
## Seat-Dodge                -1739.996606  -3654.316438    174.323225 0.1656122
## Skoda-Dodge                8118.061510   6578.375988   9657.747032 0.0000000
## SsangYong-Dodge            2111.310452   -856.530097   5079.151002 0.7806750
## Subaru-Dodge               1914.082652    -19.676384   3847.841688 0.0578865
## Suzuki-Dodge               -305.413192  -2354.684782   1743.858398 1.0000000
## Toyota-Dodge               4190.140503   2676.286027   5703.994979 0.0000000
## UAZ-Dodge                 -2164.888169  -5210.897872    881.121534 0.7826629
## Volkswagen-Dodge            819.748868   -587.459137   2226.956873 0.9865388
## Volvo-Dodge                2808.329587   1191.864071   4424.795102 0.0000000
## ZAZ-Dodge                 -4247.800762  -8112.675220   -382.926304 0.0103724
## Ford-Fiat                  1987.657044   1048.781338   2926.532750 0.0000000
## GAZ-Fiat                    879.711621   -968.321654   2727.744896 0.9998653
## Geely-Fiat                 4759.212256   1859.485008   7658.939504 0.0000001
## Great Wall-Fiat            3413.739999   -578.096838   7405.576835 0.2944698
## Honda-Fiat                 3505.076195   2340.314304   4669.838087 0.0000000
## Hyundai-Fiat               4916.170115   3839.348973   5992.991258 0.0000000
## Infiniti-Fiat             10784.584659   8769.674176  12799.495143 0.0000000
## Iveco-Fiat                 7042.296843   4892.583512   9192.010174 0.0000000
## Jaguar-Fiat               14802.979721  11480.696383  18125.263059 0.0000000
## Jeep-Fiat                  7902.469160   5493.352905  10311.585415 0.0000000
## Kia-Fiat                   5146.075247   4019.261213   6272.889282 0.0000000
## LADA-Fiat                  4588.661091   2483.505278   6693.816903 0.0000000
## Lancia-Fiat                -108.511910  -2685.596235   2468.572416 1.0000000
## Land Rover-Fiat           12185.280101  10273.683891  14096.876311 0.0000000
## Lexus-Fiat                14120.540566  12318.459255  15922.621877 0.0000000
## Lifan-Fiat                 5270.515891   1754.628516   8786.403266 0.0000021
## Lincoln-Fiat               6727.451943   2735.615106  10719.288780 0.0000000
## Mazda-Fiat                 1721.506822    681.833495   2761.180149 0.0000000
## Mercedes-Benz-Fiat         6379.796793   5424.422659   7335.170927 0.0000000
## Mini-Fiat                 10123.680603   7165.649222  13081.711985 0.0000000
## Mitsubishi-Fiat            2409.441910   1274.807369   3544.076452 0.0000000
## Moskvitch-Fiat            -2031.108097  -5296.143533   1233.927338 0.9591205
## Nissan-Fiat                3401.493894   2366.658047   4436.329741 0.0000000
## Opel-Fiat                  1415.972620    485.245519   2346.699722 0.0000012
## Peugeot-Fiat               1372.197447    394.978997   2349.415897 0.0000208
## Pontiac-Fiat               1353.523768  -2355.068658   5062.116195 1.0000000
## Porsche-Fiat              15619.803491  12508.935917  18730.671066 0.0000000
## Renault-Fiat               1549.203393    607.079434   2491.327351 0.0000000
## Rover-Fiat                -1275.778066  -3009.537572    457.981439 0.7025596
## Saab-Fiat                  1120.565091  -1278.659393   3519.789575 0.9999201
## Seat-Fiat                   857.995067   -717.131476   2433.121611 0.9964555
## Skoda-Fiat                10716.053184   9626.541955  11805.564412 0.0000000
## SsangYong-Fiat             4709.302126   1948.055897   7470.548355 0.0000000
## Subaru-Fiat                4512.074326   2913.378852   6110.769800 0.0000000
## Suzuki-Fiat                2292.578482    555.938835   4029.218128 0.0001379
## Toyota-Fiat                6788.132177   5735.441061   7840.823293 0.0000000
## UAZ-Fiat                    433.103505  -2411.993738   3278.200747 1.0000000
## Volkswagen-Fiat            3417.740541   2525.194979   4310.286103 0.0000000
## Volvo-Fiat                 5406.321260   4210.761152   6601.881369 0.0000000
## ZAZ-Fiat                  -1649.809089  -5358.401515   2058.783338 0.9999803
## GAZ-Ford                  -1107.945423  -2829.177986    613.287140 0.9324864
## Geely-Ford                 2771.555212    -49.053351   5592.163774 0.0641047
## Great Wall-Ford            1426.082954  -2508.656666   5360.822575 1.0000000
## Honda-Ford                 1517.419151    566.585404   2468.252897 0.0000002
## Hyundai-Ford               2928.513071   2087.704934   3769.321207 0.0000000
## Infiniti-Ford              8796.927615   6897.643854  10696.211376 0.0000000
## Iveco-Ford                 5054.639799   3012.904763   7096.374835 0.0000000
## Jaguar-Ford               12815.322677   9561.865880  16068.779474 0.0000000
## Jeep-Ford                  5914.812116   3601.533992   8228.090240 0.0000000
## Kia-Ford                   3158.418203   2254.468858   4062.367548 0.0000000
## LADA-Ford                  2601.004046    606.237006   4595.771086 0.0001958
## Lancia-Ford               -2096.168954  -4583.894455    391.556547 0.3316789
## Land Rover-Ford           10197.623057   8408.317432  11986.928682 0.0000000
## Lexus-Ford                12132.883522  10461.084610  13804.682433 0.0000000
## Lifan-Ford                 3282.858847   -168.065462   6733.783155 0.0980099
## Lincoln-Ford               4739.794899    805.055278   8674.534519 0.0014979
## Mazda-Ford                 -266.150223  -1058.826182    526.525737 1.0000000
## Mercedes-Benz-Ford         4392.139749   3713.793019   5070.486478 0.0000000
## Mini-Ford                  8136.023559   5255.508986  11016.538132 0.0000000
## Mitsubishi-Ford             421.784866   -491.894559   1335.464291 0.9999424
## Moskvitch-Ford            -4018.765142  -7213.741033   -823.789250 0.0005156
## Nissan-Ford                1413.836850    627.516445   2200.157255 0.0000000
## Opel-Ford                  -571.684424  -1214.854298     71.485450 0.2078815
## Peugeot-Ford               -615.459597  -1324.240556     93.321363 0.2583181
## Pontiac-Ford               -634.133276  -4281.196798   3012.930246 1.0000000
## Porsche-Ford              13632.146447  10594.892488  16669.400406 0.0000000
## Renault-Ford               -438.453652  -1098.008125    221.100821 0.8965993
## Rover-Ford                -3263.435111  -4861.351433  -1665.518788 0.0000000
## Saab-Ford                  -867.091953  -3170.066698   1435.882791 0.9999999
## Seat-Ford                 -1129.661977  -2553.894464    294.570510 0.4979819
## Skoda-Ford                 8728.396139   7871.395984   9585.396295 0.0000000
## SsangYong-Ford             2721.645082     43.605633   5399.684530 0.0393110
## Subaru-Ford                2524.417281   1074.161522   3974.673041 0.0000000
## Suzuki-Ford                 304.921437  -1296.119415   1905.962289 1.0000000
## Toyota-Ford                4800.475132   3990.800423   5610.149842 0.0000000
## UAZ-Ford                  -1554.553540  -4318.969006   1209.861926 0.9931549
## Volkswagen-Ford            1430.083497    843.523927   2016.643068 0.0000000
## Volvo-Ford                 3418.664216   2430.343154   4406.985279 0.0000000
## ZAZ-Ford                  -3637.466133  -7284.529655      9.597389 0.0519451
## Geely-GAZ                  3879.500635    640.739752   7118.261519 0.0017082
## Great Wall-GAZ             2534.028378  -1710.487528   6778.544284 0.9791452
## Honda-GAZ                  2625.364574    771.227522   4479.501627 0.0000158
## Hyundai-GAZ                4036.458494   2236.264694   5836.652294 0.0000000
## Infiniti-GAZ               9904.873038   7426.765252  12382.980825 0.0000000
## Iveco-GAZ                  6162.585222   3573.681719   8751.488726 0.0000000
## Jaguar-GAZ                13923.268100  10301.290667  17545.245533 0.0000000
## Jeep-GAZ                   7022.757539   4214.734200   9830.780879 0.0000000
## Kia-GAZ                    4266.363626   2435.827144   6096.900109 0.0000000
## LADA-GAZ                   3708.949470   1156.923816   6260.975124 0.0000065
## Lancia-GAZ                 -988.223530  -3941.614389   1965.167328 1.0000000
## Land Rover-GAZ            11305.568480   8910.708565  13700.428396 0.0000000
## Lexus-GAZ                 13240.828945  10932.441846  15549.216044 0.0000000
## Lifan-GAZ                  4390.804270    590.459815   8191.148726 0.0038102
## Lincoln-GAZ                5847.740322   1603.224416  10092.256228 0.0000382
## Mazda-GAZ                   841.795201   -936.427106   2620.017508 0.9998842
## Mercedes-Benz-GAZ          5500.085172   3769.798005   7230.372339 0.0000000
## Mini-GAZ                   9243.968982   5952.904778  12535.033187 0.0000000
## Mitsubishi-GAZ             1529.730290   -305.630571   3365.091150 0.3601966
## Moskvitch-GAZ             -2910.819718  -6480.358952    658.719516 0.4197465
## Nissan-GAZ                 2521.782273    746.383959   4297.180588 0.0000142
## Opel-GAZ                    536.261000  -1180.540352   2253.062352 1.0000000
## Peugeot-GAZ                 492.485827  -1249.957815   2234.929468 1.0000000
## Pontiac-GAZ                 473.812148  -3505.485747   4453.110042 1.0000000
## Porsche-GAZ               14740.091870  11311.002923  18169.180818 0.0000000
## Renault-GAZ                 669.491772  -1053.514757   2392.498301 0.9999997
## Rover-GAZ                 -2155.489687  -4410.944402     99.965027 0.0925267
## Saab-GAZ                    240.853470  -2558.687933   3040.394874 1.0000000
## Seat-GAZ                    -21.716553  -2157.642014   2114.208907 1.0000000
## Skoda-GAZ                  9836.341563   8028.528336  11644.154789 0.0000000
## SsangYong-GAZ              3829.590505    714.203742   6944.977268 0.0009207
## Subaru-GAZ                 3632.362705   1478.997626   5785.727784 0.0000000
## Suzuki-GAZ                 1412.866861   -844.802558   3670.536280 0.9552023
## Toyota-GAZ                 5908.420556   4122.555911   7694.285201 0.0000000
## UAZ-GAZ                    -446.608116  -3636.550477   2743.334245 1.0000000
## Volkswagen-GAZ             2538.028921    841.623449   4234.434392 0.0000023
## Volvo-GAZ                  4526.609640   2652.972023   6400.247256 0.0000000
## ZAZ-GAZ                   -2529.520710  -6508.818604   1449.777185 0.9435079
## Great Wall-Geely          -1345.472257  -6142.253095   3451.308580 1.0000000
## Honda-Geely               -1254.136061  -4157.757134   1649.485012 0.9999920
## Hyundai-Geely               156.957859  -2712.517502   3026.433220 1.0000000
## Infiniti-Geely             6025.372403   2688.576136   9362.168670 0.0000000
## Iveco-Geely                2283.084587  -1136.800276   5702.969451 0.8910122
## Jaguar-Geely              10043.767465   5787.958299  14299.576630 0.0000000
## Jeep-Geely                 3143.256904   -445.362079   6731.875887 0.2388796
## Kia-Geely                   386.862991  -2501.744795   3275.470777 1.0000000
## LADA-Geely                 -170.551165  -3562.604536   3221.502205 1.0000000
## Lancia-Geely              -4867.724166  -8571.196684  -1164.251647 0.0001563
## Land Rover-Geely           7426.067845   4150.622052  10701.513638 0.0000000
## Lexus-Geely                9361.328310   6148.565928  12574.090692 0.0000000
## Lifan-Geely                 511.303635  -3897.302620   4919.909890 1.0000000
## Lincoln-Geely              1968.239687  -2828.541151   6765.020525 0.9999984
## Mazda-Geely               -3037.705434  -5893.448017   -181.962851 0.0187217
## Mercedes-Benz-Geely        1620.584537  -1205.558561   4446.727635 0.9899806
## Mini-Geely                 5364.468347   1386.492137   9342.444557 0.0000738
## Mitsubishi-Geely          -2349.770346  -5241.437791    541.897100 0.4295471
## Moskvitch-Geely           -6790.320353 -11001.591120  -2579.049587 0.0000001
## Nissan-Geely              -1357.718362  -4211.703348   1496.266625 0.9998676
## Opel-Geely                -3343.239636  -6161.146307   -525.332964 0.0021271
## Peugeot-Geely             -3387.014809  -6220.616928   -553.412689 0.0017938
## Pontiac-Geely             -3405.688488  -7969.459172   1158.082197 0.6668115
## Porsche-Geely             10860.591235   6767.689803  14953.492668 0.0000000
## Renault-Geely             -3210.008863  -6031.700311   -388.317416 0.0052663
## Rover-Geely               -6034.990322  -9209.933959  -2860.046686 0.0000000
## Saab-Geely                -3638.647165  -7220.633094    -56.661236 0.0395856
## Seat-Geely                -3901.217189  -6992.393130   -810.041247 0.0004727
## Skoda-Geely                5956.840927   3082.579320   8831.102535 0.0000000
## SsangYong-Geely             -49.910130  -3883.814903   3783.994643 1.0000000
## Subaru-Geely               -247.137930  -3350.389820   2856.113959 1.0000000
## Suzuki-Geely              -2466.633775  -5643.151102    709.883553 0.5582141
## Toyota-Geely               2028.919921   -831.587667   4889.427508 0.7869335
## UAZ-Geely                 -4326.108751  -8220.838959   -431.378543 0.0084772
## Volkswagen-Geely          -1341.471715  -4146.998876   1464.055447 0.9998481
## Volvo-Geely                 647.109004  -2269.002970   3563.220978 1.0000000
## ZAZ-Geely                 -6409.021345 -10972.792029  -1845.250660 0.0000207
## Honda-Great Wall             91.336197  -3903.330066   4086.002459 1.0000000
## Hyundai-Great Wall         1502.430116  -2467.485759   5472.345992 0.9999999
## Infiniti-Great Wall        7370.844660   3051.058492  11690.630829 0.0000000
## Iveco-Great Wall           3628.556845   -755.728239   8012.841928 0.3790832
## Jaguar-Great Wall         11389.239722   6325.816486  16452.662958 0.0000000
## Jeep-Great Wall            4488.729161    -28.408142   9005.866465 0.0547567
## Kia-Great Wall             1732.335249  -2251.431582   5716.102079 0.9999901
## LADA-Great Wall            1174.921092  -3187.689283   5537.531467 1.0000000
## Lancia-Great Wall         -3522.251908  -8131.161965   1086.658148 0.6027919
## Land Rover-Great Wall      8771.540103   4498.966129  13044.114076 0.0000000
## Lexus-Great Wall          10706.800567   6482.089294  14931.511840 0.0000000
## Lifan-Great Wall           1856.775892  -3335.733359   7049.285144 1.0000000
## Lincoln-Great Wall         3313.711944  -2212.177090   8839.600979 0.9774907
## Mazda-Great Wall          -1692.233177  -5652.234303   2267.767949 0.9999942
## Mercedes-Benz-Great Wall   2966.056794   -972.652135   6904.765723 0.6428317
## Mini-Great Wall            6709.940605   1877.690824  11542.190385 0.0000298
## Mitsubishi-Great Wall     -1004.298088  -4990.284018   2981.687841 1.0000000
## Moskvitch-Great Wall      -5444.848096 -10470.894722   -418.801470 0.0135452
## Nissan-Great Wall           -12.246104  -3970.979932   3946.487723 1.0000000
## Opel-Great Wall           -1997.767378  -5930.570606   1935.035849 0.9992828
## Peugeot-Great Wall        -2041.542551  -5985.606976   1902.521874 0.9988738
## Pontiac-Great Wall        -2060.216230  -7385.096142   3264.663682 0.9999998
## Porsche-Great Wall        12206.063493   7278.773634  17133.353352 0.0000000
## Renault-Great Wall        -1864.536606  -5800.052562   2070.979350 0.9998816
## Rover-Great Wall          -4689.518065  -8885.541219   -493.494911 0.0075199
## Saab-Great Wall           -2293.174907  -6805.044410   2218.694596 0.9992732
## Seat-Great Wall           -2555.744931  -6688.747704   1577.257841 0.9627519
## Skoda-Great Wall           7302.313185   3328.936409  11275.689961 0.0000000
## SsangYong-Great Wall       1295.562127  -3418.795626   6009.919881 1.0000000
## Subaru-Great Wall          1098.334327  -3043.708105   5240.376759 1.0000000
## Suzuki-Great Wall         -1121.161517  -5318.375539   3076.052505 1.0000000
## Toyota-Great Wall          3374.392178   -589.046591   7337.830947 0.3054490
## UAZ-Great Wall            -2980.636494  -7744.591428   1783.318440 0.9553579
## Volkswagen-Great Wall         4.000543  -3919.942101   3927.943186 1.0000000
## Volvo-Great Wall           1992.581262  -2011.173509   5996.336032 0.9995686
## ZAZ-Great Wall            -5063.549087 -10388.428999    261.330824 0.0984923
## Hyundai-Honda              1411.093920    323.830845   2498.356995 0.0002230
## Infiniti-Honda             7279.508464   5258.998261   9300.018666 0.0000000
## Iveco-Honda                3537.220648   1382.257857   5692.183439 0.0000001
## Jaguar-Honda              11297.903526   7972.221069  14623.585982 0.0000000
## Jeep-Honda                 4397.392965   1983.591326   6811.194604 0.0000000
## Kia-Honda                  1640.999052    504.202197   2777.795908 0.0000082
## LADA-Honda                 1083.584896  -1026.931206   3194.100998 0.9990721
## Lancia-Honda              -3613.588105  -6195.052968  -1032.123241 0.0000230
## Land Rover-Honda           8680.203906   6762.706242  10597.701570 0.0000000
## Lexus-Honda               10615.464371   8807.124172  12423.804569 0.0000000
## Lifan-Honda                1765.439696  -1753.659799   5284.539191 0.9994728
## Lincoln-Honda              3222.375748   -772.290515   7217.042011 0.4501210
## Mazda-Honda               -1783.569373  -2834.053952   -733.084795 0.0000000
## Mercedes-Benz-Honda        2874.720598   1907.592396   3841.848799 0.0000000
## Mini-Honda                 6618.604408   3656.755851   9580.452966 0.0000000
## Mitsubishi-Honda          -1095.634285  -2240.183438     48.914869 0.0906066
## Moskvitch-Honda           -5536.184292  -8804.678383  -2267.690202 0.0000000
## Nissan-Honda               -103.582301  -1149.279414    942.114812 1.0000000
## Opel-Honda                -2089.103575  -3031.892077  -1146.315073 0.0000000
## Peugeot-Honda             -2132.878748  -3121.591609  -1144.165887 0.0000000
## Pontiac-Honda             -2151.552427  -5863.190206   1560.085353 0.9877092
## Porsche-Honda             12114.727296   9000.229859  15229.224733 0.0000000
## Renault-Honda             -1955.872803  -2909.914089  -1001.831516 0.0000000
## Rover-Honda               -4780.854262  -6521.118393  -3040.590130 0.0000000
## Saab-Honda                -2384.511104  -4788.440251     19.418044 0.0561787
## Seat-Honda                -2647.081128  -4229.364557  -1064.797699 0.0000000
## Skoda-Honda                7210.976988   6111.144302   8310.809675 0.0000000
## SsangYong-Honda            1204.225931  -1561.109123   3969.560985 0.9999897
## Subaru-Honda               1006.998131   -598.749185   2612.745446 0.9537581
## Suzuki-Honda              -1212.497714  -2955.631238    530.635811 0.8254003
## Toyota-Honda               3283.055982   2219.685958   4346.426006 0.0000000
## UAZ-Honda                 -3071.972690  -5921.038422   -222.906959 0.0147454
## Volkswagen-Honda            -87.335654   -992.451559    817.780252 1.0000000
## Volvo-Honda                1901.245065    696.271541   3106.218590 0.0000003
## ZAZ-Honda                 -5154.885284  -8866.523064  -1443.247504 0.0000296
## Infiniti-Hyundai           5868.414544   3897.289234   7839.539854 0.0000000
## Iveco-Hyundai              2126.126728     17.397694   4234.855762 0.0443046
## Jaguar-Hyundai             9886.809606   6590.897393  13182.721818 0.0000000
## Jeep-Hyundai               2986.299045    613.681954   5358.916136 0.0005071
## Kia-Hyundai                 229.905132   -816.603635   1276.413899 1.0000000
## LADA-Hyundai               -327.509024  -2390.795656   1735.777608 1.0000000
## Lancia-Hyundai            -5024.682025  -7567.679145  -2481.684905 0.0000000
## Land Rover-Hyundai         7269.109986   5403.722412   9134.497560 0.0000000
## Lexus-Hyundai              9204.370451   7451.382207  10957.358695 0.0000000
## Lifan-Hyundai               354.345776  -3136.633280   3845.324831 1.0000000
## Lincoln-Hyundai            1811.281828  -2158.634048   5781.197704 0.9999588
## Mazda-Hyundai             -3194.663293  -4146.709174  -2242.617413 0.0000000
## Mercedes-Benz-Hyundai      1463.626678    604.434925   2322.818430 0.0000000
## Mini-Hyundai               5207.510488   2279.128616   8135.892360 0.0000000
## Mitsubishi-Hyundai        -2506.728205  -3561.652976  -1451.803433 0.0000000
## Moskvitch-Hyundai         -6947.278212 -10185.476342  -3709.080083 0.0000000
## Nissan-Hyundai            -1514.676221  -2461.436994   -567.915448 0.0000002
## Opel-Hyundai              -3500.197495  -4331.896760  -2668.498229 0.0000000
## Peugeot-Hyundai           -3543.972668  -4427.390253  -2660.555082 0.0000000
## Pontiac-Hyundai           -3562.646347  -7247.633255    122.340562 0.0797285
## Porsche-Hyundai           10703.633376   7620.944972  13786.321780 0.0000000
## Renault-Hyundai           -3366.966723  -4211.400429  -2522.533016 0.0000000
## Rover-Hyundai             -6191.948181  -7874.622468  -4509.273895 0.0000000
## Saab-Hyundai              -3795.605024  -6158.177532  -1433.032516 0.0000001
## Seat-Hyundai              -4058.175048  -5576.889754  -2539.460342 0.0000000
## Skoda-Hyundai              5799.883068   4793.649771   6806.116365 0.0000000
## SsangYong-Hyundai          -206.867989  -2936.327912   2522.591933 1.0000000
## Subaru-Hyundai             -404.095789  -1947.241262   1139.049683 1.0000000
## Suzuki-Hyundai            -2623.591634  -4309.233349   -937.949918 0.0000005
## Toyota-Hyundai             1871.962062    905.717105   2838.207019 0.0000000
## UAZ-Hyundai               -4483.066610  -7297.324781  -1668.808440 0.0000002
## Volkswagen-Hyundai        -1498.429574  -2287.168004   -709.691143 0.0000000
## Volvo-Hyundai               490.151145   -630.042902   1610.345193 0.9999880
## ZAZ-Hyundai               -6565.979204 -10250.966112  -2880.992295 0.0000000
## Iveco-Infiniti            -3742.287816  -6452.833632  -1031.742000 0.0000357
## Jaguar-Infiniti            4018.395062    308.495091   7728.295033 0.0135842
## Jeep-Infiniti             -2882.115499  -5802.668930     38.437932 0.0603942
## Kia-Infiniti              -5638.509412  -7637.384366  -3639.634458 0.0000000
## LADA-Infiniti             -6195.923568  -8871.268819  -3520.578318 0.0000000
## Lancia-Infiniti          -10893.096569 -13953.677369  -7832.515768 0.0000000
## Land Rover-Infiniti        1400.695442  -1125.169021   3926.559905 0.9948431
## Lexus-Infiniti             3335.955907    891.924756   5779.987058 0.0000511
## Lifan-Infiniti            -5514.068768  -9398.300384  -1629.837152 0.0000145
## Lincoln-Infiniti          -4057.132716  -8376.918885    262.653453 0.1145421
## Mazda-Infiniti            -9063.077837 -11014.157498  -7111.998177 0.0000000
## Mercedes-Benz-Infiniti    -4404.787866  -6312.281235  -2497.294498 0.0000000
## Mini-Infiniti              -660.904056  -4048.490346   2726.682234 1.0000000
## Mitsubishi-Infiniti       -8375.142749 -10378.436725  -6371.848772 0.0000000
## Moskvitch-Infiniti       -12815.692756 -16474.414885  -9156.970628 0.0000000
## Nissan-Infiniti           -7383.090765  -9331.596973  -5434.584556 0.0000000
## Opel-Infiniti             -9368.612039 -11263.880925  -7473.343152 0.0000000
## Peugeot-Infiniti          -9412.387212 -11330.914541  -7493.859882 0.0000000
## Pontiac-Infiniti          -9431.060891 -13490.549652  -5371.572130 0.0000000
## Porsche-Infiniti           4835.218832   1313.388587   8357.049078 0.0000426
## Renault-Infiniti          -9235.381267 -11136.272838  -7334.489695 0.0000000
## Rover-Infiniti           -12060.362726 -14454.462397  -9666.263054 0.0000000
## Saab-Infiniti             -9664.019568 -12576.418809  -6751.620327 0.0000000
## Seat-Infiniti             -9926.589592 -12208.434206  -7644.744978 0.0000000
## Skoda-Infiniti              -68.531476  -2046.617907   1909.554956 1.0000000
## SsangYong-Infiniti        -6075.282533  -9292.466388  -2858.098679 0.0000000
## Subaru-Infiniti           -6272.510333  -8570.687531  -3974.333135 0.0000000
## Suzuki-Infiniti           -8492.006178 -10888.192413  -6095.819942 0.0000000
## Toyota-Infiniti           -3996.452482  -5954.499928  -2038.405036 0.0000000
## UAZ-Infiniti             -10351.481154 -13640.914166  -7062.048143 0.0000000
## Volkswagen-Infiniti       -7366.844118  -9243.657586  -5490.030649 0.0000000
## Volvo-Infiniti            -5378.263399  -7416.683176  -3339.843622 0.0000000
## ZAZ-Infiniti             -12434.393748 -16493.882509  -8374.904987 0.0000000
## Jaguar-Iveco               7760.682878   3975.876285  11545.489471 0.0000000
## Jeep-Iveco                  860.172317  -2154.962090   3875.306724 1.0000000
## Kia-Iveco                 -1896.221596  -4030.912261    238.469069 0.2091736
## LADA-Iveco                -2453.635752  -5231.922159    324.650655 0.2211719
## Lancia-Iveco              -7150.808753 -10301.770191  -3999.847314 0.0000000
## Land Rover-Iveco           5142.983258   2508.330637   7777.635880 0.0000000
## Lexus-Iveco                7078.243723   4521.939473   9634.547972 0.0000000
## Lifan-Iveco               -1771.780952  -5727.619473   2184.057568 0.9999760
## Lincoln-Iveco              -314.844900  -4699.129984   4069.440184 1.0000000
## Mazda-Iveco               -5320.790021  -7410.793608  -3230.786435 0.0000000
## Mercedes-Benz-Iveco        -662.500050  -2711.874126   1386.874025 1.0000000
## Mini-Iveco                 3081.383760   -388.074990   6550.842510 0.2095018
## Mitsubishi-Iveco          -4632.854933  -6771.684030  -2494.025835 0.0000000
## Moskvitch-Iveco           -9073.404940 -12808.060314  -5338.749567 0.0000000
## Nissan-Iveco              -3640.802949  -5728.404346  -1553.201551 0.0000000
## Opel-Iveco                -5626.324223  -7664.325033  -3588.323412 0.0000000
## Peugeot-Iveco             -5670.099396  -7729.747488  -3610.451303 0.0000000
## Pontiac-Iveco             -5688.773075  -9816.829779  -1560.716371 0.0000379
## Porsche-Iveco              8577.506648   4976.855120  12178.158177 0.0000000
## Renault-Iveco             -5493.093451  -7536.324206  -3449.862695 0.0000000
## Rover-Iveco               -8318.074910 -10826.683366  -5809.466453 0.0000000
## Saab-Iveco                -5921.731752  -8928.968439  -2914.495065 0.0000000
## Seat-Iveco                -6184.301776  -8586.013247  -3782.590304 0.0000000
## Skoda-Iveco                3673.756340   1558.518982   5788.993699 0.0000000
## SsangYong-Iveco           -2332.994717  -5636.277191    970.287757 0.7957455
## Subaru-Iveco              -2530.222517  -4947.456802   -112.988233 0.0245814
## Suzuki-Iveco              -4749.718362  -7260.318215  -2239.118508 0.0000000
## Toyota-Iveco               -254.164666  -2350.674373   1842.345040 1.0000000
## UAZ-Iveco                 -6609.193339  -9982.881630  -3235.505047 0.0000000
## Volkswagen-Iveco          -3624.556302  -5645.405615  -1603.706989 0.0000000
## Volvo-Iveco               -1635.975583  -3807.739460    535.788294 0.6419781
## ZAZ-Iveco                 -8692.105932 -12820.162636  -4564.049228 0.0000000
## Jeep-Jaguar               -6900.510561 -10838.445891  -2962.575230 0.0000000
## Kia-Jaguar                -9656.904474 -12969.487062  -6344.321885 0.0000000
## LADA-Jaguar              -10214.318630 -13973.996081  -6454.641180 0.0000000
## Lancia-Jaguar            -14911.491630 -18954.368967 -10868.614294 0.0000000
## Land Rover-Jaguar         -2617.699620  -6272.517482   1037.118243 0.7660110
## Lexus-Jaguar               -682.439155  -4281.187631   2916.309321 1.0000000
## Lifan-Jaguar              -9532.463830 -14229.798986  -4835.128673 0.0000000
## Lincoln-Jaguar            -8075.527778 -13138.951014  -3012.104542 0.0000002
## Mazda-Jaguar             -13081.472899 -16365.436079  -9797.509719 0.0000000
## Mercedes-Benz-Jaguar      -8423.182928 -11681.439099  -5164.926757 0.0000000
## Mini-Jaguar               -4679.299118  -8975.046223   -383.552012 0.0122529
## Mitsubishi-Jaguar        -12393.537810 -15708.788793  -9078.286827 0.0000000
## Moskvitch-Jaguar         -16834.087818 -21346.731160 -12321.444476 0.0000000
## Nissan-Jaguar            -11401.485827 -14683.920711  -8119.050942 0.0000000
## Opel-Jaguar              -13387.007100 -16638.121752 -10135.892449 0.0000000
## Peugeot-Jaguar           -13430.782273 -16695.510354 -10166.054193 0.0000000
## Pontiac-Jaguar           -13449.455952 -18292.714290  -8606.197615 0.0000000
## Porsche-Jaguar              816.823770  -3585.560879   5219.208420 1.0000000
## Renault-Jaguar           -13253.776328 -16508.171985  -9999.380671 0.0000000
## Rover-Jaguar             -16078.757787 -19643.784514 -12513.731061 0.0000000
## Saab-Jaguar              -13682.414630 -17614.306243  -9750.523016 0.0000000
## Seat-Jaguar              -13944.984653 -17435.617428 -10454.351879 0.0000000
## Skoda-Jaguar              -4086.926537  -7387.006575   -786.846500 0.0007656
## SsangYong-Jaguar         -10093.677595 -14256.365942  -5930.989248 0.0000000
## Subaru-Jaguar            -10290.905395 -13792.236679  -6789.574112 0.0000000
## Suzuki-Jaguar            -12510.401239 -16076.829537  -8943.972942 0.0000000
## Toyota-Jaguar             -8014.847544 -11302.955226  -4726.739863 0.0000000
## UAZ-Jaguar               -14369.876216 -18588.652325 -10151.100107 0.0000000
## Volkswagen-Jaguar        -11385.239179 -14625.629761  -8144.848598 0.0000000
## Volvo-Jaguar              -9396.658460 -12733.252159  -6060.064762 0.0000000
## ZAZ-Jaguar               -16452.788810 -21296.047147 -11609.530472 0.0000000
## Kia-Jeep                  -2756.393913  -5152.114672   -360.673154 0.0041632
## LADA-Jeep                 -3313.808069  -6297.337704   -330.278434 0.0084859
## Lancia-Jeep               -8010.981070 -11344.317493  -4677.644647 0.0000000
## Land Rover-Jeep            4282.810941   1432.553381   7133.068501 0.0000019
## Lexus-Jeep                 6218.071406   3440.074800   8996.068011 0.0000000
## Lifan-Jeep                -2631.953269  -6734.541735   1470.635197 0.9355891
## Lincoln-Jeep              -1175.017217  -5692.154520   3342.120086 1.0000000
## Mazda-Jeep                -6180.962338  -8536.952303  -3824.972373 0.0000000
## Mercedes-Benz-Jeep        -1522.672367  -3842.695605    797.350871 0.9122320
## Mini-Jeep                  2221.211443  -1414.681534   5857.104421 0.9693222
## Mitsubishi-Jeep           -5493.027250  -7892.436267  -3093.618233 0.0000000
## Moskvitch-Jeep            -9933.577257 -13823.336181  -6043.818334 0.0000000
## Nissan-Jeep               -4500.975266  -6854.834505  -2147.116027 0.0000000
## Opel-Jeep                 -6486.496540  -8796.479446  -4176.513634 0.0000000
## Peugeot-Jeep              -6530.271713  -8859.375400  -4201.168025 0.0000000
## Pontiac-Jeep              -6548.945392 -10817.835865  -2280.054918 0.0000009
## Porsche-Jeep               7717.334331   3956.049291  11478.619371 0.0000000
## Renault-Jeep              -6353.265768  -8667.864143  -4038.667392 0.0000000
## Rover-Jeep                -9178.247226 -11912.418054  -6444.076399 0.0000000
## Saab-Jeep                 -6781.904069  -9979.723046  -3584.085092 0.0000000
## Seat-Jeep                 -7044.474093  -9680.909511  -4408.038674 0.0000000
## Skoda-Jeep                 2813.584023    435.180608   5191.987438 0.0022719
## SsangYong-Jeep            -3193.167034  -6670.845689    284.511621 0.1484416
## Subaru-Jeep               -3390.394834  -6040.978790   -739.810879 0.0003314
## Suzuki-Jeep               -5609.890679  -8345.888732  -2873.892625 0.0000000
## Toyota-Jeep               -1114.336983  -3476.100450   1247.426484 0.9998942
## UAZ-Jeep                  -7469.365655 -11013.987837  -3924.743474 0.0000000
## Volkswagen-Jeep           -4484.728619  -6779.593684  -2189.863553 0.0000000
## Volvo-Jeep                -2496.147900  -4924.960791    -67.335008 0.0330525
## ZAZ-Jeep                  -9552.278249 -13821.168722  -5283.387775 0.0000000
## LADA-Kia                   -557.414156  -2647.227024   1532.398711 1.0000000
## Lancia-Kia                -5254.587157  -7819.153484  -2690.020829 0.0000000
## Land Rover-Kia             7039.204854   5144.518364   8933.891345 0.0000000
## Lexus-Kia                  8974.465319   7190.331389  10758.599248 0.0000000
## Lifan-Kia                   124.440644  -3382.281595   3631.162883 1.0000000
## Lincoln-Kia                1581.376696  -2402.390134   5565.143526 0.9999995
## Mazda-Kia                 -3424.568425  -4432.813165  -2416.323686 0.0000000
## Mercedes-Benz-Kia          1233.721546    312.647953   2154.795138 0.0000903
## Mini-Kia                   4977.605356   2030.473448   7924.737264 0.0000000
## Mitsubishi-Kia            -2736.633337  -3842.541276  -1630.725398 0.0000000
## Moskvitch-Kia             -7177.183344 -10432.347430  -3922.019259 0.0000000
## Nissan-Kia                -1744.581353  -2747.837081   -741.325624 0.0000000
## Opel-Kia                  -3730.102627  -4625.585605  -2834.619649 0.0000000
## Peugeot-Kia               -3773.877800  -4717.590005  -2830.165595 0.0000000
## Pontiac-Kia               -3792.551479  -7492.456155    -92.646802 0.0344354
## Porsche-Kia               10473.728244   7373.222819  13574.233669 0.0000000
## Renault-Kia               -3596.871855  -4504.194499  -2689.549211 0.0000000
## Rover-Kia                 -6421.853314  -8136.950643  -4706.755984 0.0000000
## Saab-Kia                  -4025.510156  -6411.283605  -1639.736707 0.0000000
## Seat-Kia                  -4288.080180  -5842.641357  -2733.519003 0.0000000
## Skoda-Kia                  5569.977936   4510.415978   6629.539895 0.0000000
## SsangYong-Kia              -436.773121  -3186.339917   2312.793675 1.0000000
## Subaru-Kia                 -634.000922  -2212.438138    944.436295 0.9999992
## Suzuki-Kia                -2853.496766  -4571.505522  -1135.488009 0.0000000
## Toyota-Kia                 1642.056930    620.393867   2663.719992 0.0000001
## UAZ-Kia                   -4712.971743  -7546.735167  -1879.208318 0.0000000
## Volkswagen-Kia            -1728.334706  -2584.065041   -872.604370 0.0000000
## Volvo-Kia                   260.246013   -908.086474   1428.578500 1.0000000
## ZAZ-Kia                   -6795.884336 -10495.789012  -3095.979660 0.0000000
## Lancia-LADA               -4697.173000  -7817.905538  -1576.440462 0.0000018
## Land Rover-LADA            7596.619011   4998.194868  10195.043153 0.0000000
## Lexus-LADA                 9531.879475   7012.930289  12050.828662 0.0000000
## Lifan-LADA                  681.854800  -3249.947838   4613.657439 1.0000000
## Lincoln-LADA               2138.790852  -2223.819523   6501.401227 0.9997062
## Mazda-LADA                -2867.154269  -4911.299220   -823.009318 0.0000215
## Mercedes-Benz-LADA         1791.135702   -211.449549   3793.720954 0.1954875
## Mini-LADA                  5535.019513   2092.991388   8977.047637 0.0000001
## Mitsubishi-LADA           -2179.219180  -4273.259174    -85.179187 0.0270442
## Moskvitch-LADA            -6619.769188 -10328.955669  -2910.582707 0.0000000
## Nissan-LADA               -1187.167196  -3228.856003    854.521610 0.9869881
## Opel-LADA                 -3172.688470  -5163.633193  -1181.743747 0.0000002
## Peugeot-LADA              -3216.463643  -5229.561716  -1203.365570 0.0000002
## Pontiac-LADA              -3235.137322  -7340.166645    869.892000 0.5162748
## Porsche-LADA              11031.142401   7456.914510  14605.370292 0.0000000
## Renault-LADA              -3039.457698  -5035.755648  -1043.159748 0.0000012
## Rover-LADA                -5864.439157  -8334.971484  -3393.906831 0.0000000
## Saab-LADA                 -3468.095999  -6443.644029   -492.547970 0.0031559
## Seat-LADA                 -3730.666023  -6092.578719  -1368.753328 0.0000003
## Skoda-LADA                 6127.392093   4057.454251   8197.329935 0.0000000
## SsangYong-LADA              120.641035  -3153.819026   3395.101096 1.0000000
## Subaru-LADA                 -76.586765  -2454.282114   2301.108584 1.0000000
## Suzuki-LADA               -2296.082609  -4768.637000    176.471781 0.1307398
## Toyota-LADA                2199.471086    148.674524   4250.267648 0.0162158
## UAZ-LADA                  -4155.557586  -7501.030090   -810.085082 0.0007103
## Volkswagen-LADA           -1170.920549  -3144.304833    802.463735 0.9812616
## Volvo-LADA                  817.660170  -1310.008020   2945.328359 0.9999998
## ZAZ-LADA                  -6238.470179 -10343.499502  -2133.440857 0.0000013
## Land Rover-Lancia         12293.792011   9300.217116  15287.366905 0.0000000
## Lexus-Lancia              14229.052476  11304.195619  17153.909332 0.0000000
## Lifan-Lancia               5379.027801   1175.606026   9582.449575 0.0003275
## Lincoln-Lancia             6835.963853   2227.053796  11444.873909 0.0000031
## Mazda-Lancia               1830.018731   -697.472358   4357.509820 0.7414507
## Mercedes-Benz-Lancia       6488.308702   3994.309842   8982.307563 0.0000000
## Mini-Lancia               10232.192513   6482.893881  13981.491145 0.0000000
## Mitsubishi-Lancia          2517.953820    -50.058275   5085.965915 0.0660196
## Moskvitch-Lancia          -1922.596188  -5918.562526   2073.370150 0.9998206
## Nissan-Lancia              3510.005804    984.500744   6035.510864 0.0000289
## Opel-Lancia                1524.484530   -960.177120   4009.146180 0.9671034
## Peugeot-Lancia             1480.709357  -1021.738740   3983.157454 0.9821601
## Pontiac-Lancia             1462.035678  -2903.848925   5827.920281 1.0000000
## Porsche-Lancia            15728.315401  11857.296460  19599.334342 0.0000000
## Renault-Lancia             1657.715302   -831.237918   4146.668522 0.8941317
## Rover-Lancia              -1167.266157  -4050.530384   1715.998070 0.9999990
## Saab-Lancia                1229.077001  -2097.117326   4555.271328 1.0000000
## Seat-Lancia                 966.506977  -1824.248155   3757.262109 1.0000000
## Skoda-Lancia              10824.565093   8276.168480  13372.961706 0.0000000
## SsangYong-Lancia           4817.814036   1221.736823   8413.891248 0.0000897
## Subaru-Lancia              4620.586235   1816.461096   7424.711375 0.0000000
## Suzuki-Lancia              2401.090391   -483.906635   5286.087417 0.3640619
## Toyota-Lancia              6896.644086   4363.770389   9429.517783 0.0000000
## UAZ-Lancia                  541.615414  -3119.240893   4202.471721 1.0000000
## Volkswagen-Lancia          3526.252451   1055.639539   5996.865363 0.0000121
## Volvo-Lancia               5514.833170   2919.326562   8110.339778 0.0000000
## ZAZ-Lancia                -1541.297179  -5907.181782   2824.587424 1.0000000
## Lexus-Land Rover           1935.260465   -424.320871   4294.841801 0.4037990
## Lifan-Land Rover          -6914.764210 -10746.420649  -3083.107772 0.0000000
## Lincoln-Land Rover        -5457.828158  -9730.402132  -1185.254185 0.0003435
## Mazda-Land Rover         -10463.773280 -12307.966235  -8619.580324 0.0000000
## Mercedes-Benz-Land Rover  -5805.483308  -7603.500763  -4007.465854 0.0000000
## Mini-Land Rover           -2061.599498  -5388.771974   1265.572978 0.9615544
## Mitsubishi-Land Rover     -9775.838191 -11675.186124  -7876.490258 0.0000000
## Moskvitch-Land Rover     -14216.388199 -17819.245873 -10613.530524 0.0000000
## Nissan-Land Rover         -8783.786207 -10625.256342  -6942.316072 0.0000000
## Opel-Land Rover          -10769.307481 -12554.350888  -8984.264073 0.0000000
## Peugeot-Land Rover       -10813.082654 -12622.801673  -9003.363635 0.0000000
## Pontiac-Land Rover       -10831.756333 -14840.968826  -6822.543840 0.0000000
## Porsche-Land Rover         3434.523390    -29.235275   6898.282056 0.0564708
## Renault-Land Rover       -10636.076709 -12427.088876  -8845.064542 0.0000000
## Rover-Land Rover         -13461.058168 -15768.881612 -11153.234723 0.0000000
## Saab-Land Rover          -11064.715010 -13906.616689  -8222.813331 0.0000000
## Seat-Land Rover          -11327.285034 -13518.437848  -9136.132220 0.0000000
## Skoda-Land Rover          -1469.226918  -3341.968690    403.514854 0.5291439
## SsangYong-Land Rover      -7475.977975 -10629.485192  -4322.470759 0.0000000
## Subaru-Land Rover         -7673.205776  -9881.362076  -5465.049475 0.0000000
## Suzuki-Land Rover         -9892.701620 -12202.689561  -7582.713678 0.0000000
## Toyota-Land Rover         -5397.147925  -7248.710944  -3545.584905 0.0000000
## UAZ-Land Rover           -11752.176597 -14979.358858  -8524.994335 0.0000000
## Volkswagen-Land Rover     -8767.539560 -10532.975656  -7002.103464 0.0000000
## Volvo-Land Rover          -6778.958841  -8715.319087  -4842.598595 0.0000000
## ZAZ-Land Rover           -13835.089190 -17844.301683  -9825.876697 0.0000000
## Lifan-Lexus               -8850.024675 -12628.236956  -5071.812393 0.0000000
## Lincoln-Lexus             -7393.088623 -11617.799896  -3168.377350 0.0000000
## Mazda-Lexus              -12399.033744 -14129.451219 -10668.616269 0.0000000
## Mercedes-Benz-Lexus       -7740.743773  -9421.863563  -6059.623984 0.0000000
## Mini-Lexus                -3996.859963  -7262.342112   -731.377814 0.0010229
## Mitsubishi-Lexus         -11711.098655 -13500.182095  -9922.015216 0.0000000
## Moskvitch-Lexus          -16151.648663 -19697.615443 -12605.681883 0.0000000
## Nissan-Lexus             -10719.046672 -12446.562009  -8991.531334 0.0000000
## Opel-Lexus               -12704.567945 -14371.804266 -11037.331625 0.0000000
## Peugeot-Lexus            -12748.343119 -14441.972331 -11054.713906 0.0000000
## Pontiac-Lexus            -12767.016797 -16725.183266  -8808.850328 0.0000000
## Porsche-Lexus              1499.262925  -1905.281255   4903.807106 0.9999855
## Renault-Lexus            -12571.337173 -14244.962449 -10897.711898 0.0000000
## Rover-Lexus              -15396.318632 -17614.278513 -13178.358751 0.0000000
## Saab-Lexus               -12999.975475 -15769.398182 -10230.552767 0.0000000
## Seat-Lexus               -13262.545499 -15358.839285 -11166.251713 0.0000000
## Skoda-Lexus               -3404.487382  -5165.299334  -1643.675431 0.0000000
## SsangYong-Lexus           -9411.238440 -12499.588282  -6322.888598 0.0000000
## Subaru-Lexus              -9608.466240 -11722.526606  -7494.405875 0.0000000
## Suzuki-Lexus             -11827.962084 -14048.174072  -9607.750097 0.0000000
## Toyota-Lexus              -7332.408389  -9070.678390  -5594.138388 0.0000000
## UAZ-Lexus                -13687.437061 -16850.979748 -10523.894375 0.0000000
## Volkswagen-Lexus         -10702.800025 -12349.026495  -9056.573554 0.0000000
## Volvo-Lexus               -8714.219306 -10542.548593  -6885.890018 0.0000000
## ZAZ-Lexus                -15770.349655 -19728.516124 -11812.183186 0.0000000
## Lincoln-Lifan              1456.936052  -3735.573199   6649.445303 1.0000000
## Mazda-Lifan               -3549.009069  -7028.709002    -69.309137 0.0372180
## Mercedes-Benz-Lifan        1109.280902  -2346.168523   4564.730327 1.0000000
## Mini-Lifan                 4853.164712    405.992504   9300.336920 0.0118440
## Mitsubishi-Lifan          -2861.073981  -6370.316995    648.169034 0.4203071
## Moskvitch-Lifan           -7301.623988 -11958.645288  -2644.602688 0.0000004
## Nissan-Lifan              -1869.021997  -5347.279639   1609.235645 0.9973614
## Opel-Lifan                -3854.543271  -7303.259543   -405.826998 0.0075114
## Peugeot-Lifan             -3898.318444  -7359.871114   -436.765773 0.0064635
## Pontiac-Lifan             -3916.992123  -8895.048850   1061.064605 0.5207528
## Porsche-Lifan             10349.287600   5799.025184  14899.550017 0.0000000
## Renault-Lifan             -3721.312498  -7173.121958   -269.503039 0.0147853
## Rover-Lifan               -6546.293957 -10292.400338  -2800.187577 0.0000000
## Saab-Lifan                -4149.950800  -8246.738458    -53.163142 0.0413032
## Seat-Lifan                -4412.520824  -8087.900344   -737.141303 0.0016203
## Skoda-Lifan                5445.537292   1950.623029   8940.451556 0.0000005
## SsangYong-Lifan            -561.213765  -4879.995044   3757.567513 1.0000000
## Subaru-Lifan               -758.441565  -4443.983345   2927.100215 1.0000000
## Suzuki-Lifan              -2977.937410  -6725.377636    769.502817 0.4926531
## Toyota-Lifan               1517.616286  -1965.995286   5001.227857 0.9999895
## UAZ-Lifan                 -4837.412386  -9210.279788   -464.544985 0.0091701
## Volkswagen-Lifan          -1852.775350  -5291.383872   1585.833173 0.9971986
## Volvo-Lifan                 135.805369  -3393.607467   3665.218205 1.0000000
## ZAZ-Lifan                 -6920.324980 -11898.381707  -1942.268253 0.0000287
## Mazda-Lincoln             -5005.945121  -8965.946247  -1045.943996 0.0004529
## Mercedes-Benz-Lincoln      -347.655150  -4286.364079   3591.053778 1.0000000
## Mini-Lincoln               3396.228660  -1436.021121   8228.478441 0.8055568
## Mitsubishi-Lincoln        -4318.010033  -8303.995962   -332.024103 0.0135516
## Moskvitch-Lincoln         -8758.560040 -13784.606666  -3732.513415 0.0000000
## Nissan-Lincoln            -3325.958049  -7284.691877    632.775779 0.3392060
## Opel-Lincoln              -5311.479323  -9244.282550  -1378.676095 0.0000705
## Peugeot-Lincoln           -5355.254496  -9299.318921  -1411.190071 0.0000600
## Pontiac-Lincoln           -5373.928175 -10698.808086    -49.048263 0.0436795
## Porsche-Lincoln            8892.351548   3965.061689  13819.641407 0.0000000
## Renault-Lincoln           -5178.248550  -9113.764507  -1242.732594 0.0001516
## Rover-Lincoln             -8003.230009 -12199.253164  -3807.206855 0.0000000
## Saab-Lincoln              -5606.886852 -10118.756355  -1095.017349 0.0007024
## Seat-Lincoln              -5869.456876 -10002.459648  -1736.454103 0.0000143
## Skoda-Lincoln              3988.601240     15.224464   7961.978017 0.0472805
## SsangYong-Lincoln         -2018.149817  -6732.507571   2696.207936 0.9999939
## Subaru-Lincoln            -2215.377617  -6357.420049   1926.664814 0.9976187
## Suzuki-Lincoln            -4434.873462  -8632.087484   -237.659439 0.0209974
## Toyota-Lincoln               60.680234  -3902.758535   4024.119003 1.0000000
## UAZ-Lincoln               -6294.348438 -11058.303372  -1530.393505 0.0001346
## Volkswagen-Lincoln        -3309.711402  -7233.654045    614.231242 0.3290519
## Volvo-Lincoln             -1321.130683  -5324.885453   2682.624088 1.0000000
## ZAZ-Lincoln               -8377.261032 -13702.140944  -3052.381120 0.0000003
## Mercedes-Benz-Mazda        4658.289971   3846.140156   5470.439786 0.0000000
## Mini-Mazda                 8402.173781   5487.247154  11317.100408 0.0000000
## Mitsubishi-Mazda            687.935089   -329.042358   1704.912536 0.8722236
## Moskvitch-Mazda           -3752.614919  -6978.650254   -526.579584 0.0032942
## Nissan-Mazda               1679.987072    775.701268   2584.272877 0.0000000
## Opel-Mazda                 -305.534201  -1088.541559    477.473157 0.9999997
## Peugeot-Mazda              -349.309374  -1187.046496    488.427747 0.9999973
## Pontiac-Mazda              -367.983053  -4042.286439   3306.320333 1.0000000
## Porsche-Mazda             13898.296670  10828.387119  16968.206220 0.0000000
## Renault-Mazda              -172.303429   -968.824075    624.217216 1.0000000
## Rover-Mazda               -2997.284888  -4656.432142  -1338.137635 0.0000000
## Saab-Mazda                 -600.941731  -2946.815919   1744.932458 1.0000000
## Seat-Mazda                 -863.511754  -2356.117266    629.093757 0.9881564
## Skoda-Mazda                8994.546362   8028.170502   9960.922221 0.0000000
## SsangYong-Mazda            2987.795304    272.776276   5702.814332 0.0101279
## Subaru-Mazda               2790.567504   1273.110814   4308.024193 0.0000000
## Suzuki-Mazda                571.071660  -1091.085025   2233.228345 1.0000000
## Toyota-Mazda               5066.625355   4141.959917   5991.290793 0.0000000
## UAZ-Mazda                 -1288.403317  -4088.657932   1511.851297 0.9999476
## Volkswagen-Mazda           1696.233720    959.019256   2433.448184 0.0000000
## Volvo-Mazda                3684.814439   2600.281563   4769.347314 0.0000000
## ZAZ-Mazda                 -3371.315910  -7045.619296    302.987475 0.1496025
## Mini-Mercedes-Benz         3743.883810    857.949586   6629.818035 0.0002256
## Mitsubishi-Mercedes-Benz  -3970.354882  -4900.979531  -3039.730233 0.0000000
## Moskvitch-Mercedes-Benz   -8410.904890 -11610.767870  -5211.041910 0.0000000
## Nissan-Mercedes-Benz      -2978.302899  -3784.250741  -2172.355056 0.0000000
## Opel-Mercedes-Benz        -4963.824172  -5630.847135  -4296.801210 0.0000000
## Peugeot-Mercedes-Benz     -5007.599345  -5738.094105  -4277.104586 0.0000000
## Pontiac-Mercedes-Benz     -5026.273024  -8677.618596  -1374.927453 0.0000392
## Porsche-Mercedes-Benz      9240.006699   6197.612286  12282.401111 0.0000000
## Renault-Mercedes-Benz     -4830.593400  -5513.428848  -4147.757953 0.0000000
## Rover-Mercedes-Benz       -7655.574859  -9263.240471  -6047.909248 0.0000000
## Saab-Mercedes-Benz        -5259.231702  -7568.981649  -2949.481754 0.0000000
## Seat-Mercedes-Benz        -5521.801725  -6956.963849  -4086.639602 0.0000000
## Skoda-Mercedes-Benz        4336.256391   3461.212728   5211.300053 0.0000000
## SsangYong-Mercedes-Benz   -1670.494667  -4354.362665   1013.373331 0.9587720
## Subaru-Mercedes-Benz      -1867.722467  -3328.713197   -406.731737 0.0003364
## Suzuki-Mercedes-Benz      -4087.218311  -5697.989541  -2476.447081 0.0000000
## Toyota-Mercedes-Benz        408.335384   -420.413843   1237.084611 0.9996658
## UAZ-Mercedes-Benz         -5946.693288  -8716.755565  -3176.631012 0.0000000
## Volkswagen-Mercedes-Benz  -2962.056251  -3574.677076  -2349.435427 0.0000000
## Volvo-Mercedes-Benz        -973.475532  -1977.482837     30.531772 0.0767602
## ZAZ-Mercedes-Benz         -8029.605881 -11680.951453  -4378.260310 0.0000000
## Mitsubishi-Mini           -7714.238693 -10664.369564  -4764.107822 0.0000000
## Moskvitch-Mini           -12154.788701 -16406.415802  -7903.161599 0.0000000
## Nissan-Mini               -6722.186709  -9635.391447  -3808.981971 0.0000000
## Opel-Mini                 -8707.707983 -11585.576908  -5829.839058 0.0000000
## Peugeot-Mini              -8751.483156 -11644.722260  -5858.244052 0.0000000
## Pontiac-Mini              -8770.156835 -13371.193066  -4169.120604 0.0000000
## Porsche-Mini               5496.122888   1361.709547   9630.536230 0.0001127
## Renault-Mini              -8574.477211 -11456.052156  -5692.902265 0.0000000
## Rover-Mini               -11399.458670 -14627.739735  -8171.177604 0.0000000
## Saab-Mini                 -9003.115512 -12632.461836  -5373.769188 0.0000000
## Seat-Mini                 -9265.685536 -12411.619458  -6119.751614 0.0000000
## Skoda-Mini                  592.372580  -2340.699415   3525.444576 1.0000000
## SsangYong-Mini            -5414.378477  -9292.568435  -1536.188519 0.0000250
## Subaru-Mini               -5611.606278  -8769.406751  -2453.805804 0.0000000
## Suzuki-Mini               -7831.102122 -11060.930890  -4601.273353 0.0000000
## Toyota-Mini               -3335.548427  -6255.143467   -415.953386 0.0048240
## UAZ-Mini                  -9690.577099 -13628.908590  -5752.245607 0.0000000
## Volkswagen-Mini           -6705.940062  -9571.688514  -3840.191609 0.0000000
## Volvo-Mini                -4717.359343  -7691.454262  -1743.264424 0.0000002
## ZAZ-Mini                 -11773.489692 -16374.525923  -7172.453461 0.0000000
## Moskvitch-Mitsubishi      -4440.550008  -7698.429517  -1182.670499 0.0000533
## Nissan-Mitsubishi           992.051984    -19.979503   2004.083471 0.0662495
## Opel-Mitsubishi            -993.469290  -1898.773348    -88.165232 0.0106769
## Peugeot-Mitsubishi        -1037.244463  -1990.280874    -84.208052 0.0124465
## Pontiac-Mitsubishi        -1055.918142  -4758.212064   2646.375780 1.0000000
## Porsche-Mitsubishi        13210.361581  10107.005403  16313.717758 0.0000000
## Renault-Mitsubishi         -860.238518  -1777.255450     56.778414 0.1161701
## Rover-Mitsubishi          -3685.219977  -5405.465461  -1964.974493 0.0000000
## Saab-Mitsubishi           -1288.876819  -3678.353880   1100.600242 0.9971318
## Seat-Mitsubishi           -1551.446843  -3111.685968      8.792282 0.0542447
## Skoda-Mitsubishi           8306.611273   7238.736178   9374.486368 0.0000000
## SsangYong-Mitsubishi       2299.860215   -452.920785   5052.641216 0.3538729
## Subaru-Mitsubishi          2102.632415    518.602832   3686.661998 0.0001177
## Suzuki-Mitsubishi          -116.863429  -1840.011641   1606.284783 1.0000000
## Toyota-Mitsubishi          4378.690266   3348.408224   5408.972309 0.0000000
## UAZ-Mitsubishi            -1976.338406  -4813.220642    860.543830 0.8225290
## Volkswagen-Mitsubishi      1008.298631    142.296275   1874.300987 0.0032283
## Volvo-Mitsubishi           2996.879350   1821.002454   4172.756246 0.0000000
## ZAZ-Mitsubishi            -4059.250999  -7761.544921   -356.957077 0.0108557
## Nissan-Moskvitch           5432.601992   2208.122408   8657.081575 0.0000000
## Opel-Moskvitch             3447.080718    254.489875   6639.671561 0.0143880
## Peugeot-Moskvitch          3403.305545    196.852792   6609.758297 0.0194418
## Pontiac-Moskvitch          3384.631866  -1419.537276   8188.801007 0.8007550
## Porsche-Moskvitch         17650.911589  13291.567553  22010.255624 0.0000000
## Renault-Moskvitch          3580.311490    384.379559   6776.243421 0.0071757
## Rover-Moskvitch             755.330031  -2756.408196   4267.068258 1.0000000
## Saab-Moskvitch             3151.673189   -731.967047   7035.313424 0.4332515
## Seat-Moskvitch             2889.103165   -547.087601   6325.293931 0.3372613
## Skoda-Moskvitch           12747.161281   9504.721139  15989.601422 0.0000000
## SsangYong-Moskvitch        6740.410223   2623.267514  10857.552933 0.0000001
## Subaru-Moskvitch           6543.182423   3096.124174   9990.240672 0.0000000
## Suzuki-Moskvitch           4323.686579    810.525521   7836.847636 0.0008942
## Toyota-Moskvitch           8819.240274   5588.986114  12049.494434 0.0000000
## UAZ-Moskvitch              2464.211602  -1709.630953   6638.054157 0.9828478
## Volkswagen-Moskvitch       5448.848639   2267.179119   8630.518159 0.0000000
## Volvo-Moskvitch            7437.429358   4157.833753  10717.024962 0.0000000
## ZAZ-Moskvitch               381.299009  -4422.870133   5185.468150 1.0000000
## Opel-Nissan               -1985.521274  -2762.093953  -1208.948595 0.0000000
## Peugeot-Nissan            -2029.296447  -2861.022416  -1197.570478 0.0000000
## Pontiac-Nissan            -2047.970126  -5720.907639   1624.967387 0.9942324
## Porsche-Nissan            12218.309597   9150.034959  15286.584235 0.0000000
## Renault-Nissan            -1852.290502  -2642.486516  -1062.094487 0.0000000
## Rover-Nissan              -4677.271961  -6333.392189  -3021.151732 0.0000000
## Saab-Nissan               -2280.928803  -4624.663070     62.805464 0.0730542
## Seat-Nissan               -2543.498827  -4032.738840  -1054.258814 0.0000000
## Skoda-Nissan               7314.559289   6353.389739   8275.728840 0.0000000
## SsangYong-Nissan           1307.808232  -1405.362041   4020.978504 0.9998115
## Subaru-Nissan              1110.580431   -403.565997   2624.726860 0.7105451
## Suzuki-Nissan             -1108.915413  -2768.050564    550.219738 0.8894359
## Toyota-Nissan              3386.638282   2467.415364   4305.861201 0.0000000
## UAZ-Nissan                -2968.390390  -5766.852558   -169.928221 0.0196541
## Volkswagen-Nissan            16.246647   -714.129810    746.623104 1.0000000
## Volvo-Nissan               2004.827366    924.931000   3084.723732 0.0000000
## ZAZ-Nissan                -5051.302983  -8724.240496  -1378.365470 0.0000404
## Peugeot-Opel                -43.775173   -741.726314    654.175968 1.0000000
## Pontiac-Opel                -62.448852  -3707.423157   3582.525453 1.0000000
## Porsche-Opel              14203.830871  11169.085913  17238.575829 0.0000000
## Renault-Opel                133.230772   -514.671573    781.133117 1.0000000
## Rover-Opel                -2691.750687  -4284.892840  -1098.608534 0.0000000
## Saab-Opel                  -295.407529  -2595.072292   2004.257233 1.0000000
## Seat-Opel                  -557.977553  -1976.851586    860.896480 0.9999996
## Skoda-Opel                 9300.080563   8452.015346  10148.145780 0.0000000
## SsangYong-Opel             3293.329505    618.135936   5968.523075 0.0008879
## Subaru-Opel                3096.101705   1651.107894   4541.095516 0.0000000
## Suzuki-Opel                 876.605861   -719.670167   2472.881889 0.9957900
## Toyota-Opel                5372.159556   4571.948033   6172.371079 0.0000000
## UAZ-Opel                   -982.869116  -3744.527715   1778.789483 1.0000000
## Volkswagen-Opel            2001.767921   1428.341835   2575.194007 0.0000000
## Volvo-Opel                 3990.348640   3009.765207   4970.932073 0.0000000
## ZAZ-Opel                  -3065.781709  -6710.756014    579.192596 0.3363006
## Pontiac-Peugeot             -18.673679  -3675.795586   3638.448228 1.0000000
## Porsche-Peugeot           14247.606044  11198.281541  17296.930546 0.0000000
## Renault-Peugeot             177.005945   -536.072179    890.084069 1.0000000
## Rover-Peugeot             -2647.975514  -4268.717591  -1027.233437 0.0000001
## Saab-Peugeot               -251.632356  -2570.502982   2067.238270 1.0000000
## Seat-Peugeot               -514.202380  -1963.997705    935.592945 1.0000000
## Skoda-Peugeot              9343.855736   8445.013384  10242.698088 0.0000000
## SsangYong-Peugeot          3337.104679    645.383371   6028.825986 0.0007453
## Subaru-Peugeot             3139.876878   1664.509102   4615.244655 0.0000000
## Suzuki-Peugeot              920.381034   -703.441653   2544.203721 0.9919986
## Toyota-Peugeot             5415.934729   4562.095492   6269.773967 0.0000000
## UAZ-Peugeot                -939.093943  -3716.765842   1838.577956 1.0000000
## Volkswagen-Peugeot         2045.543094   1399.384880   2691.701308 0.0000000
## Volvo-Peugeot              4034.123813   3009.308302   5058.939324 0.0000000
## ZAZ-Peugeot               -3022.006536  -6679.128443    635.115371 0.3833205
## Porsche-Pontiac           14266.279723   9565.526399  18967.033046 0.0000000
## Renault-Pontiac             195.679624  -3452.221457   3843.580705 1.0000000
## Rover-Pontiac             -2629.301835  -6556.833728   1298.230058 0.8872161
## Saab-Pontiac               -232.958677  -4496.274625   4030.357270 1.0000000
## Seat-Pontiac               -495.528701  -4355.659317   3364.601915 1.0000000
## Skoda-Pontiac              9362.529415   5673.814265  13051.244565 0.0000000
## SsangYong-Pontiac          3355.778357  -1121.281558   7832.838272 0.6552194
## Subaru-Pontiac             3158.550557   -711.257185   7028.358300 0.4172162
## Suzuki-Pontiac              939.054713  -2989.749431   4867.858857 1.0000000
## Toyota-Pontiac             5434.608408   1756.600343   9112.616474 0.0000036
## UAZ-Pontiac                -920.420264  -5449.676612   3608.836084 1.0000000
## Volkswagen-Pontiac         2064.216773  -1571.195490   5699.629036 0.9917152
## Volvo-Pontiac              4052.797492    331.379924   7774.215060 0.0123026
## ZAZ-Pontiac               -3003.332857  -8119.311994   2112.646280 0.9845072
## Renault-Porsche          -14070.600099 -17108.859728 -11032.340469 0.0000000
## Rover-Porsche            -16895.581558 -20264.460607 -13526.702509 0.0000000
## Saab-Porsche             -14499.238400 -18254.195410 -10744.281390 0.0000000
## Seat-Porsche             -14761.808424 -18051.861258 -11471.755590 0.0000000
## Skoda-Porsche             -4903.750308  -7990.894415  -1816.606201 0.0000002
## SsangYong-Porsche        -10910.501365 -14906.487447  -6914.515284 0.0000000
## Subaru-Porsche           -11107.729166 -14409.130571  -7806.327760 0.0000000
## Suzuki-Porsche           -13327.225010 -16697.587199  -9956.862821 0.0000000
## Toyota-Porsche            -8831.671315 -11906.013945  -5757.328684 0.0000000
## UAZ-Porsche              -15186.699987 -19241.080623 -11132.319351 0.0000000
## Volkswagen-Porsche       -12202.062950 -15225.316430  -9178.809470 0.0000000
## Volvo-Porsche            -10213.482231 -13339.628100  -7087.336362 0.0000000
## ZAZ-Porsche              -17269.612580 -21970.365904 -12568.859256 0.0000000
## Rover-Renault             -2824.981459  -4424.808492  -1225.154426 0.0000000
## Saab-Renault               -428.638301  -2732.939201   1875.662598 1.0000000
## Seat-Renault               -691.208325  -2117.584201    735.167550 0.9997831
## Skoda-Renault              9166.849791   8306.292281  10027.407301 0.0000000
## SsangYong-Renault          3160.098733    480.918775   5839.278692 0.0024267
## Subaru-Renault             2962.870933   1510.510189   4415.231677 0.0000000
## Suzuki-Renault              743.375089   -859.572749   2346.322927 0.9999345
## Toyota-Renault             5238.928784   4425.489728   6052.367840 0.0000000
## UAZ-Renault               -1116.099888  -3881.620243   1649.420467 0.9999991
## Volkswagen-Renault         1868.537149   1276.792194   2460.282104 0.0000000
## Volvo-Renault              3857.117868   2865.710542   4848.525193 0.0000000
## ZAZ-Renault               -3199.012481  -6846.913562    448.888600 0.2362584
## Saab-Rover                 2396.343158   -329.115906   5121.802221 0.2305897
## Seat-Rover                 2133.773134     95.913323   4171.632945 0.0244561
## Skoda-Rover               11991.831250  10301.007871  13682.654629 0.0000000
## SsangYong-Rover            5985.080192   2936.091881   9034.068503 0.0000000
## Subaru-Rover               5787.852392   3731.721024   7843.983760 0.0000000
## Suzuki-Rover               3568.356548   1403.231553   5733.481543 0.0000000
## Toyota-Rover               8063.910243   6396.574774   9731.245713 0.0000000
## UAZ-Rover                  1708.881571  -1416.246795   4834.009937 0.9961523
## Volkswagen-Rover           4693.518608   3122.376806   6264.660410 0.0000000
## Volvo-Rover                6682.099327   4921.073218   8443.125435 0.0000000
## ZAZ-Rover                  -374.031022  -4301.562915   3553.500870 1.0000000
## Seat-Saab                  -262.570024  -2889.969634   2364.829586 1.0000000
## Skoda-Saab                 9595.488092   7227.104720  11963.871465 0.0000000
## SsangYong-Saab             3588.737035    117.903443   7059.570626 0.0300215
## Subaru-Saab                3391.509234    749.912690   6033.105778 0.0002998
## Suzuki-Saab                1172.013390  -1555.278736   3899.305517 0.9999931
## Toyota-Saab                5667.567085   3315.894560   8019.239611 0.0000000
## UAZ-Saab                   -687.461587  -4225.368228   2850.445055 1.0000000
## Volkswagen-Saab            2297.175450     12.696809   4581.654092 0.0460979
## Volvo-Saab                 4285.756169   1866.754504   6704.757834 0.0000000
## ZAZ-Saab                  -2770.374180  -7033.690127   1492.941768 0.9231164
## Skoda-Seat                 9858.058116   8330.319492  11385.796740 0.0000000
## SsangYong-Seat             3851.307059    889.646828   6812.967289 0.0002112
## Subaru-Seat                3654.079258   1729.818932   5578.339585 0.0000000
## Suzuki-Seat                1434.583414   -605.727309   3474.894137 0.8047263
## Toyota-Seat                5930.137109   4428.435018   7431.839201 0.0000000
## UAZ-Seat                   -424.891563  -3464.879870   2615.096744 1.0000000
## Volkswagen-Seat            2559.745474   1165.619165   3953.871783 0.0000000
## Volvo-Seat                 4548.326193   2943.235990   6153.416396 0.0000000
## ZAZ-Seat                  -2507.804156  -6367.934772   1352.326460 0.9233538
## SsangYong-Skoda           -6006.751058  -8741.242311  -3272.259805 0.0000000
## Subaru-Skoda              -6203.978858  -7756.006207  -4651.951508 0.0000000
## Suzuki-Skoda              -8423.474702 -10117.251233  -6729.698171 0.0000000
## Toyota-Skoda              -3927.921007  -4908.288418  -2947.553595 0.0000000
## UAZ-Skoda                -10282.949679 -13102.087844  -7463.811514 0.0000000
## Volkswagen-Skoda          -7298.312642  -8104.289847  -6492.335437 0.0000000
## Volvo-Skoda               -5309.731923  -6442.130108  -4177.333739 0.0000000
## ZAZ-Skoda                -12365.862272 -16054.577423  -8677.147122 0.0000000
## Subaru-SsangYong           -197.227800  -3171.489879   2777.034279 1.0000000
## Suzuki-SsangYong          -2416.723644  -5467.350622    633.903333 0.5014539
## Toyota-SsangYong           2078.830051   -641.200516   4798.860617 0.6026456
## UAZ-SsangYong             -4276.198621  -8068.953032   -483.444211 0.0063170
## Volkswagen-SsangYong      -1291.561585  -3953.712083   1370.588914 0.9997763
## Volvo-SsangYong             697.019134  -2081.428574   3475.466843 1.0000000
## ZAZ-SsangYong             -6359.111215 -10836.171130  -1882.051300 0.0000142
## Suzuki-Subaru             -2219.495844  -4278.056370   -160.935318 0.0147601
## Toyota-Subaru              2276.057851    749.652674   3802.463028 0.0000026
## UAZ-Subaru                -4078.970821  -7131.237601  -1026.704041 0.0000966
## Volkswagen-Subaru         -1094.333784  -2515.034934    326.367366 0.5808875
## Volvo-Subaru                894.246935   -733.978526   2522.472395 0.9957805
## ZAZ-Subaru                -6161.883414 -10031.691157  -2292.075672 0.0000002
## Toyota-Suzuki              4495.553695   2825.223547   6165.883844 0.0000000
## UAZ-Suzuki                -1859.474977  -4986.202106   1267.252152 0.9805028
## Volkswagen-Suzuki          1125.162060   -449.157412   2699.481532 0.7707122
## Volvo-Suzuki               3113.742779   1349.881052   4877.604506 0.0000000
## ZAZ-Suzuki                -3942.387570  -7871.191715    -13.583426 0.0475404
## UAZ-Toyota                -6355.028672  -9160.142549  -3549.914795 0.0000000
## Volkswagen-Toyota         -3370.391635  -4125.853828  -2614.929443 0.0000000
## Volvo-Toyota              -1381.810916  -2478.829384   -284.792449 0.0004972
## ZAZ-Toyota                -8437.941265 -12115.949331  -4759.933200 0.0000000
## Volkswagen-UAZ             2984.637037    235.611235   5733.662839 0.0130147
## Volvo-UAZ                  4973.217756   2111.422995   7835.012516 0.0000000
## ZAZ-UAZ                   -2082.912593  -6612.168941   2446.343755 0.9999483
## Volvo-Volkswagen           1988.580719   1044.161050   2933.000388 0.0000000
## ZAZ-Volkswagen            -5067.549630  -8702.961893  -1432.137367 0.0000263
## ZAZ-Volvo                 -7056.130349 -10777.547917  -3334.712781 0.0000000

With the results see that numerous manufacturers are statistically different and we can use this data to list every statistically different manufacturer.

We can confirm that there is a relationship between the manufacturer and asking price.

Q3: What is the relationship between odometer and price?

A: There is a low negative correlation between price and odometer.

Justification:

Initially a Scatter plot was used to quickly inspect for possible relationships between price and odometer.

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

When we investigate this graph we initially notice that the line of best fit seems to be going down as the odometer value increases. Nevertheless, the data had a significant amount of variation and further testing would need to be done to confirm our results.

Since we are investigating the relationship between 2 continuous variables we begin by using a correlation test.

The hypotheses for the test are as follows:

H0 =There does not exist a correlation between Odometer Value and Vehicle Price

Ha = There does exist a correlation between Odometer Value and Vehicle Price

Furthermore, we will use 0.05 as our significance level. The result of the correlation test was the following:

#Getting cor value
cor.test(cars_edited$odometer_value, cars_edited$price_usd)
## 
##  Pearson's product-moment correlation
## 
## data:  cars_edited$odometer_value and cars_edited$price_usd
## t = -90.821, df = 38488, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.4282966 -0.4118421
## sample estimates:
##        cor 
## -0.4201039

Since the p-value is less than 0.05 we can conclude that Price and Odometer are significantly correlated with a correlation coefficient of -0.4201039 and p-value of < 2.2e-16

We continue with our question by investigating how good of an indicator of price odometer is. To do this we will use linear regression, and check the percentage of accuracy of that line. Afterwords, we will graph the linear regression line to provide us with a useful visual.

## `geom_smooth()` using formula 'y ~ x'

Once the linear regression model is created and graphed we proceed to check the R2 to see the proportion of the prices that can be explained by the model, the variability of the beta coefficients, and the percentage error.

summary(odometer_on_price)
## 
## Call:
## lm(formula = price_usd ~ odometer_value, data = cars_edited)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -11577  -3514  -1122   2064  40854 
## 
## Coefficients:
##                  Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     1.158e+04  6.203e+01  186.65   <2e-16 ***
## odometer_value -1.986e-02  2.186e-04  -90.82   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5830 on 38488 degrees of freedom
## Multiple R-squared:  0.1765, Adjusted R-squared:  0.1765 
## F-statistic:  8248 on 1 and 38488 DF,  p-value: < 2.2e-16
confint(odometer_on_price)
##                        2.5 %        97.5 %
## (Intercept)     1.145654e+04  1.169971e+04
## odometer_value -2.028451e-02 -1.942748e-02
#                       2.5 %        97.5 %
#(Intercept)     1.145654e+04  1.169971e+04
#odometer_value -2.028451e-02 -1.942748e-02

sigma(odometer_on_price)*100/mean(cars_edited$price_usd)
## [1] 87.89188
#[1] 87.89188

The R2 is 0.1765 which indicates that a low proportion of prices in the data can be explained by the model. Furthermore, the percentage error is 87.89188 which confirms how poor a model would be if it solely used odometer to predict price.

We can conclude that the higher the odometer the lower the price of the vehicle will be. Nevertheless, our linear regression model informs us that in order to create an accurate model we will need to consider more attributes.

Q4: Does the number of photos a vehicle has impact the selling price?

A: There exists a low positive correlation between number of photos a vehicle has and the selling price.

Justification:

In order to gain an intuitive understanding of the question we sought to use a scatter plot to see the relationship between price and number of photos.

#Scatter plot: Number of photos and price
ggplot(cars_edited, aes( x =number_of_photos, y=price_usd)) + geom_hex() + stat_smooth(color = "red") 
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

When we look at this graph we can see that although there exists a line. Nevertheless, the data had a significant amount of variation and further testing would need to be done to get a result. It does seem that there will be a very little(if any) correlation between price and number of photos.

Since we are investigating the relationship between 2 continuous variables we will be using the correlation test.

The hypotheses are as follows:

H0 =There does not exist a correlation between Number of Photos and Vehicle Price

Ha = There does exist a correlation between Number of Photos and Vehicle Price

We will use 0.05 as our significance level. The result of the correlation test was the following:

#getting the cor value
cor.test(cars_edited$number_of_photos, cars_edited$price_usd)
## 
##  Pearson's product-moment correlation
## 
## data:  cars_edited$number_of_photos and cars_edited$price_usd
## t = 65.382, df = 38488, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.3071525 0.3251358
## sample estimates:
##       cor 
## 0.3161726

Since the p-value is less than 0.05 we can conclude that Price and Number of Photos are significantly correlated with a correlation coefficient of 0.3161726 and p-value of < 2.2e-16

Next we aim to investigate how good of an indicator of price the number of vehicle photos is. We shall employ linear regression, check the percentage of accuracy of that line, and graph the linear regression line to provide us with a useful visual.

#Getting the formula for linear regression
number_of_photos_on_price <- lm (price_usd ~ number_of_photos, data = cars_edited)

#Scatter plot: Number of photos and price with linear regression line
ggplot (cars_edited, aes(x=number_of_photos, y=price_usd)) + geom_point() + stat_smooth(method=lm)
## `geom_smooth()` using formula 'y ~ x'

Although the linear regression model is created and graphed there remains information and insights to be gleaned. We proceed to check the R2 to see the proportion of the prices that can be explained by the model, the variability of the beta coefficients, and the percentage error.

summary(number_of_photos_on_price)
## 
## Call:
## lm(formula = price_usd ~ number_of_photos, data = cars_edited)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -24082  -3884  -1585   2249  44082 
## 
## Coefficients:
##                  Estimate Std. Error t value Pr(>|t|)    
## (Intercept)      3418.275     58.159   58.77   <2e-16 ***
## number_of_photos  333.297      5.098   65.38   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6095 on 38488 degrees of freedom
## Multiple R-squared:  0.09997,    Adjusted R-squared:  0.09994 
## F-statistic:  4275 on 1 and 38488 DF,  p-value: < 2.2e-16
# R^2 is very low(0.09994) which tells us that number of photos is not a good indicator of price. 
# We can suspect that several more variables are in play.

confint(number_of_photos_on_price)
##                     2.5 %    97.5 %
## (Intercept)      3304.283 3532.2680
## number_of_photos  323.305  343.2882
#                    2.5 %    97.5 %
#(Intercept)      3304.283 3532.2680
#number_of_photos  323.305  343.2882
sigma(number_of_photos_on_price)*100/mean(cars_edited$price_usd)
## [1] 91.88472
# Our prediction error rate is extremely high (91.82279%) which explains the low correlation

The R2 is 0.09994 which indicates that a low proportion of prices in the data can be explained by the model. In other words, number of photos is not a good indicator of price(more attributes are needed in a model). Also, the percentage error is 91.88472 which is very high. This confirms how poor a model would be if it solely used number of photos to predict price.

We can conclude there is a low negative correlation between price and odometer. Our linear regression model tells us that to create an accurate model we will need to consider more attributes.

Q5: Does the number of times a vehicle has been upped in the catalog to raise its position impact the selling price?

A: The number of times a vehicle has been upped has a negligible impact on the selling price.

Justification:

Graphs used: Scatter plot How these graphs helped us solve the problem: Using a scatter plot for this question again allowed us to see the relationship between the two variables. With that we can come up with a solution to the question.

To begin answering this questions it was natural to use scatterplot (using 2 continuous attributes) to gain an intuitive understanding of any possible relationship.

#Regression analysis
ggplot(cars_edited, aes( x =up_counter, y=price_usd)) + geom_hex() + stat_smooth(color = "red")
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'

Looking at the Scatterplot we see a possible positive correlation although the variability of the data makes it hard for us to affirm this prediction. To continue we will use the correlation test(since we are dealing with continuous attributes) to check for a correlation between number of up counts and price of a vehicle.

The hypotheses for the correlation test are the following:

H0 =There does not exist a correlation between number of up counts and vehicle price

Ha = There does exist a correlation between number of up counts and vehicle price

We will use 0.05 as our significance level. The results are the following:

#Correlation
cor.test(cars_edited$up_counter, cars_edited$price_usd)
## 
##  Pearson's product-moment correlation
## 
## data:  cars_edited$up_counter and cars_edited$price_usd
## t = 11.352, df = 38488, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.04780740 0.06772124
## sample estimates:
##        cor 
## 0.05777007

Since the p-value is less than 0.05 we can conclude that Price and number of up counts are correlated with a correlation coefficient of 0.05777007 and p-value of < 2.2e-16.

However, although they are correlated we do see that the correlation coefficient is very close to 0. Meaning that the correlation is almost entirely negligible. If one were to attempt to use this as a predictor of price the results would be poor.

Nevertheless,we will use linear regression to see how poor of an indicator number of up counts really is. We will check the percentage of accuracy of the linear regression line, and graph the linear regression line to provide useful insights.

# Create LM
up_counter_on_price <- lm (price_usd ~ up_counter, data = cars_edited)
#Finding how well this line fits the data
summary(up_counter_on_price)
## 
## Call:
## lm(formula = price_usd ~ up_counter, data = cars_edited)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -14558  -4502  -1852   2305  43438 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 6493.0457    34.9345  185.86   <2e-16 ***
## up_counter     8.5694     0.7548   11.35   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6413 on 38488 degrees of freedom
## Multiple R-squared:  0.003337,   Adjusted R-squared:  0.003311 
## F-statistic: 128.9 on 1 and 38488 DF,  p-value: < 2.2e-16
# R^2 is extremely low which affirms that number of photos is not a good indicator of price. 

confint(up_counter_on_price)
##                   2.5 %     97.5 %
## (Intercept) 6424.573138 6561.51822
## up_counter     7.089888   10.04893
sigma(up_counter_on_price)*100/mean(cars_edited$price_usd)
## [1] 96.69137
# Our prediction error rate is extremely high (96.65168%) which confirms to us that up_counter is a terrible predictor of price(as we can see by the correlation test)

#Scatter plot: up counter and price with regression line
ggplot (cars_edited, aes(x=up_counter, y=price_usd)) + geom_point() + stat_smooth(method=lm)
## `geom_smooth()` using formula 'y ~ x'

The R2 is 0.003311 which indicates that a low proportion of prices in the data can be explained by the model. In other words, number of up counts is a very poor indicator of price(we need more attributes in the model). Also, the percentage error is 96.69137 which is ludicrously high. This confirms how poor a model would be if it solely used number of up counts to predict price.

We can conclude there is a negligible positive correlation between price and number of up counts.

Q6: Relationship between Engine Type and Body Type? What is the impact of Engine Type and Body Type on the selling price?

A: Sedan and Gasoline is the most common followed by Gasoline and Hatchback. Engine Type and Body Type do have an impact on the selling price, but the extend of this impact will need to be investigated in our overall model.

Justification:

To begin this question it was important to have a working knowledge of how body type and engine type related to one another. Initially a Mosaic plot felt like the right graph to show relationships, but the quantity of categories made a balloon plot much easy to read. The spacious nature of the balloon plot greatly aided in gaining insights from the data and pushed further investigation.

# Balloon Plot
ggplot(cars_edited, aes(body_type, engine_type)) + geom_count()

Based on this Balloon plot we can see that several combinations of body types and engine types do not exist. Furthermore, there seems to be higher quantities of hatchbacks with gasoline engines and sedans with gasoline engines. Nevertheless, visualization does not suffice in proving any relationship. We shall proceed with a Chi-Square test for more information. The reason for a Chi-Square test is that we are attempting to analyze the frequency table of two categorical variables(engine type and body type).

The hypotheses for the Chi-Square test are as follows:

H0 = Engine Type and Body Type are independent

Ha = Engine Type and Body Type are dependent

The test will be performed with 0.05 as our significance level. The results are the following:

#Chi-Square Test
engine_body.data <- table(cars_edited$body_type, cars_edited$engine_type)
chisq.test(engine_body.data)
## Warning in chisq.test(engine_body.data): Chi-squared approximation may be
## incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  engine_body.data
## X-squared = 6965.4, df = 22, p-value < 2.2e-16

The result of the Chi-Square Test tells us that Engine Type and Body Type are dependent.

We continue with a proportion table to give us an easy way of seeing the distribution of engine type and body type.

# Table
prop.table(engine_body.data)*100
##            
##                   diesel     electric     gasoline
##   cabriolet  0.010392310  0.000000000  0.184463497
##   coupe      0.080540400  0.000000000  1.613406080
##   hatchback  4.081579631  0.020784619 15.757339569
##   liftback   0.249415433  0.005196155  1.176929072
##   limousine  0.000000000  0.000000000  0.031176929
##   minibus    3.273577553  0.000000000  0.280592362
##   minivan    5.081839439  0.000000000  4.292023902
##   pickup     0.192257729  0.000000000  0.142894258
##   sedan      6.635489738  0.000000000 27.079760977
##   suv        4.359573915  0.000000000  9.051701741
##   universal  7.622759158  0.000000000  6.677058976
##   van        1.847233048  0.000000000  0.252013510

From the table we can clearly see that Hatchback and Gasoline as well as Sedan and Gasoline are the most common combinations of the two variables as we suspected from the balloon plot.

We continue by attempting to solve that second part of the question. That is, what is the impact of Engine Type and Body Type on the selling price?

The most effective method of solving this question is with the use of the Two-Way Anova. The reason for the use of this test is because we are attempting to evaluate the simultaneous effect of two grouping variables(engine and body type) on a response variable(price).

The hypotheses for the Two-Way Anova test are:

Ho = 1. There is no difference in the means of Engine Type 2. There is no difference in the means of Body Type. 3. There is no interaction between engine and body type

Ha = For cases 1 and 2 the means are not equal and for case 3 there is an interaction between Engine and Body Type.

body_engine_type_on_price.aov <- aov(price_usd ~ engine_type * body_type, data = cars_edited)
summary(body_engine_type_on_price.aov)
##                          Df    Sum Sq   Mean Sq F value Pr(>F)    
## engine_type               2 1.301e+10 6.503e+09  204.12 <2e-16 ***
## body_type                11 3.457e+11 3.142e+10  986.32 <2e-16 ***
## engine_type:body_type    11 4.280e+09 3.891e+08   12.21 <2e-16 ***
## Residuals             38465 1.225e+12 3.186e+07                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Since the p-value is less than 0.05 for all three cases we can confirm that there is a difference in the means of Engine Type, the means of Body Type, and there is an interaction between Engine and Body Type.

To conclude our investigation we will run the Tukey Honest Significant Differences in order to perform the multiple pairwise-comparisons between the means of groups to determine which groups are different and how they differ.

#Tukey HSD
TukeyHSD(body_engine_type_on_price.aov)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = price_usd ~ engine_type * body_type, data = cars_edited)
## 
## $engine_type
##                         diff        lwr       upr p adj
## electric-diesel    10052.532   5867.612 14237.452 1e-07
## gasoline-diesel    -1175.359  -1318.298 -1032.420 0e+00
## gasoline-electric -11227.891 -15412.002 -7043.779 0e+00
## 
## $body_type
##                            diff         lwr        upr     p adj
## coupe-cabriolet     -3510.93890 -5760.05406 -1261.8237 0.0000218
## hatchback-cabriolet -7129.82230 -9270.19038 -4989.4542 0.0000000
## liftback-cabriolet  -3285.65559 -5555.93678 -1015.3744 0.0001423
## limousine-cabriolet -2758.76153 -8493.81258  2976.2895 0.9193030
## minibus-cabriolet   -3529.16912 -5716.72120 -1341.6170 0.0000088
## minivan-cabriolet   -5419.24172 -7571.21007 -3267.2734 0.0000000
## pickup-cabriolet      161.12611 -2517.35454  2839.6068 1.0000000
## sedan-cabriolet     -5362.19106 -7498.28165 -3226.1005 0.0000000
## suv-cabriolet        2473.04299   327.68105  4618.4049 0.0090611
## universal-cabriolet -6522.64572 -8667.05290 -4378.2385 0.0000000
## van-cabriolet       -5272.55651 -7499.16037 -3045.9527 0.0000000
## hatchback-coupe     -3618.88340 -4371.45730 -2866.3095 0.0000000
## liftback-coupe        225.28331  -842.12881  1292.6954 0.9999350
## limousine-coupe       752.17737 -4621.46222  6125.8170 0.9999991
## minibus-coupe         -18.23022  -896.05483   859.5944 1.0000000
## minivan-coupe       -1908.30282 -2693.26124 -1123.3444 0.0000000
## pickup-coupe         3672.06502  1894.58069  5449.5493 0.0000000
## sedan-coupe         -1851.25216 -2591.57298 -1110.9313 0.0000000
## suv-coupe            5983.98190  5217.32043  6750.6434 0.0000000
## universal-coupe     -3011.70681 -3775.69248 -2247.7211 0.0000000
## van-coupe           -1761.61761 -2732.67717  -790.5581 0.0000002
## liftback-hatchback   3844.16671  3030.51741  4657.8160 0.0000000
## limousine-hatchback  4371.06077  -957.97845  9700.1000 0.2358264
## minibus-hatchback    3600.65318  3059.14363  4142.1627 0.0000000
## minivan-hatchback    1710.58058  1338.00004  2083.1611 0.0000000
## pickup-hatchback     7290.94841  5653.23443  8928.6624 0.0000000
## sedan-hatchback      1767.63124  1501.67738  2033.5851 0.0000000
## suv-hatchback        9602.86529  9270.56071  9935.1699 0.0000000
## universal-hatchback   607.17658   281.09279   933.2604 0.0000001
## van-hatchback        1857.26579  1174.90723  2539.6243 0.0000000
## limousine-liftback    526.89406 -4855.63882  5909.4269 1.0000000
## minibus-liftback     -243.51353 -1174.23034   687.2033 0.9994686
## minivan-liftback    -2133.58613 -2977.27887 -1289.8934 0.0000000
## pickup-liftback      3446.78170  1642.58984  5250.9736 0.0000000
## sedan-liftback      -2076.53548 -2878.86498 -1274.2060 0.0000000
## suv-liftback         5758.69858  4932.00183  6585.3953 0.0000000
## universal-liftback  -3236.99013 -4061.20601 -2412.7742 0.0000000
## van-liftback        -1986.90092 -3006.02524  -967.7766 0.0000000
## minibus-limousine    -770.40759 -6118.57248  4577.7573 0.9999987
## minivan-limousine   -2660.48019 -7994.18915  2673.2288 0.8982890
## pickup-limousine     2919.88764 -2647.13509  8486.9104 0.8622214
## sedan-limousine     -2603.42954 -7930.75217  2723.8931 0.9106371
## suv-limousine        5231.80452   -99.24241 10562.8515 0.0601517
## universal-limousine -3763.88419 -9094.54697  1566.7786 0.4710753
## van-limousine       -2513.79498 -7878.05153  2850.4616 0.9321174
## minivan-minibus     -1890.07260 -2475.75583 -1304.3894 0.0000000
## pickup-minibus       3690.29524  1991.37921  5389.2113 0.0000000
## sedan-minibus       -1833.02194 -2357.36919 -1308.6747 0.0000000
## suv-minibus          6002.21211  5441.28884  6563.1354 0.0000000
## universal-minibus   -2993.47660 -3550.73706 -2436.2161 0.0000000
## van-minibus         -1743.38739 -2561.81380  -924.9610 0.0000000
## pickup-minivan       5580.36783  3927.52200  7233.2137 0.0000000
## sedan-minivan          57.05065  -290.11459   404.2159 0.9999950
## suv-minivan          7892.28471  7492.01157  8292.5579 0.0000000
## universal-minivan   -1103.40400 -1498.52789  -708.2801 0.0000000
## van-minivan           146.68521  -571.23224   864.6026 0.9999530
## sedan-pickup        -5523.31718 -7155.43682 -3891.1975 0.0000000
## suv-pickup           2311.91688   667.68168  3956.1521 0.0002708
## universal-pickup    -6683.77183 -8326.76109 -5040.7826 0.0000000
## van-pickup          -5433.68263 -7182.59551 -3684.7697 0.0000000
## suv-sedan            7835.23406  7531.69860  8138.7695 0.0000000
## universal-sedan     -1160.45465 -1457.16677  -863.7425 0.0000000
## van-sedan              89.63455  -579.18578   758.4549 0.9999994
## universal-suv       -8995.68871 -9353.08620 -8638.2912 0.0000000
## van-suv             -7745.59951 -8443.46448 -7047.7345 0.0000000
## van-universal        1250.08920   555.16487  1945.0135 0.0000003
## 
## $`engine_type:body_type`
##                                               diff          lwr           upr
## electric:cabriolet-diesel:cabriolet             NA           NA            NA
## gasoline:cabriolet-diesel:cabriolet     4886.12394  -6244.21419  16016.462082
## diesel:coupe-diesel:cabriolet           3770.43194  -7736.51410  15277.377968
## electric:coupe-diesel:cabriolet                 NA           NA            NA
## gasoline:coupe-diesel:cabriolet          974.87185  -9889.41214  11839.155845
## diesel:hatchback-diesel:cabriolet      -2230.26043 -13073.50085   8612.980002
## electric:hatchback-diesel:cabriolet     8862.50000  -4400.82863  22125.828633
## gasoline:hatchback-diesel:cabriolet    -2350.01229 -13183.04532   8483.020736
## diesel:liftback-diesel:cabriolet        1889.10417  -9163.66969  12941.878028
## electric:liftback-diesel:cabriolet     20124.50000   1367.32076  38881.679235
## gasoline:liftback-diesel:cabriolet      1362.95479  -9514.21480  12240.124385
## diesel:limousine-diesel:cabriolet               NA           NA            NA
## electric:limousine-diesel:cabriolet             NA           NA            NA
## gasoline:limousine-diesel:cabriolet     1804.08333 -10700.70282  14308.869490
## diesel:minibus-diesel:cabriolet         2288.02738  -8558.61110  13134.665864
## electric:minibus-diesel:cabriolet               NA           NA            NA
## gasoline:minibus-diesel:cabriolet        112.09306 -10916.09173  11140.277845
## diesel:minivan-diesel:cabriolet          546.59630 -10293.93360  11387.126194
## electric:minivan-diesel:cabriolet               NA           NA            NA
## gasoline:minivan-diesel:cabriolet      -1125.92030 -11968.48558   9716.644987
## diesel:pickup-diesel:cabriolet          4353.90041  -6764.39842  15472.199234
## electric:pickup-diesel:cabriolet                NA           NA            NA
## gasoline:pickup-diesel:cabriolet        6803.27600  -4413.07424  18019.626241
## diesel:sedan-diesel:cabriolet           -236.46869 -11074.40825  10601.470864
## electric:sedan-diesel:cabriolet                 NA           NA            NA
## gasoline:sedan-diesel:cabriolet         -649.26683 -11480.80710  10182.273447
## diesel:suv-diesel:cabriolet             8608.89306  -2233.46932  19451.255444
## electric:suv-diesel:cabriolet                   NA           NA            NA
## gasoline:suv-diesel:cabriolet           6844.36931  -3991.30807  17680.046692
## diesel:universal-diesel:cabriolet       -565.78852 -11402.63054  10271.053489
## electric:universal-diesel:cabriolet             NA           NA            NA
## gasoline:universal-diesel:cabriolet    -2209.42317 -13047.30997   8628.463634
## diesel:van-diesel:cabriolet              592.28395 -10267.59843  11452.166331
## electric:van-diesel:cabriolet                   NA           NA            NA
## gasoline:van-diesel:cabriolet          -1637.94608 -12688.44079   9412.548621
## gasoline:cabriolet-electric:cabriolet           NA           NA            NA
## diesel:coupe-electric:cabriolet                 NA           NA            NA
## electric:coupe-electric:cabriolet               NA           NA            NA
## gasoline:coupe-electric:cabriolet               NA           NA            NA
## diesel:hatchback-electric:cabriolet             NA           NA            NA
## electric:hatchback-electric:cabriolet           NA           NA            NA
## gasoline:hatchback-electric:cabriolet           NA           NA            NA
## diesel:liftback-electric:cabriolet              NA           NA            NA
## electric:liftback-electric:cabriolet            NA           NA            NA
## gasoline:liftback-electric:cabriolet            NA           NA            NA
## diesel:limousine-electric:cabriolet             NA           NA            NA
## electric:limousine-electric:cabriolet           NA           NA            NA
## gasoline:limousine-electric:cabriolet           NA           NA            NA
## diesel:minibus-electric:cabriolet               NA           NA            NA
## electric:minibus-electric:cabriolet             NA           NA            NA
## gasoline:minibus-electric:cabriolet             NA           NA            NA
## diesel:minivan-electric:cabriolet               NA           NA            NA
## electric:minivan-electric:cabriolet             NA           NA            NA
## gasoline:minivan-electric:cabriolet             NA           NA            NA
## diesel:pickup-electric:cabriolet                NA           NA            NA
## electric:pickup-electric:cabriolet              NA           NA            NA
## gasoline:pickup-electric:cabriolet              NA           NA            NA
## diesel:sedan-electric:cabriolet                 NA           NA            NA
## electric:sedan-electric:cabriolet               NA           NA            NA
## gasoline:sedan-electric:cabriolet               NA           NA            NA
## diesel:suv-electric:cabriolet                   NA           NA            NA
## electric:suv-electric:cabriolet                 NA           NA            NA
## gasoline:suv-electric:cabriolet                 NA           NA            NA
## diesel:universal-electric:cabriolet             NA           NA            NA
## electric:universal-electric:cabriolet           NA           NA            NA
## gasoline:universal-electric:cabriolet           NA           NA            NA
## diesel:van-electric:cabriolet                   NA           NA            NA
## electric:van-electric:cabriolet                 NA           NA            NA
## gasoline:van-electric:cabriolet                 NA           NA            NA
## diesel:coupe-gasoline:cabriolet        -1115.69201  -5778.27915   3546.895129
## electric:coupe-gasoline:cabriolet               NA           NA            NA
## gasoline:coupe-gasoline:cabriolet      -3911.25209  -6624.65927  -1197.844914
## diesel:hatchback-gasoline:cabriolet    -7116.38437  -9744.26846  -4488.500276
## electric:hatchback-gasoline:cabriolet   3976.37606  -4101.11107  12053.863181
## gasoline:hatchback-gasoline:cabriolet  -7236.13623  -9821.57940  -4650.693069
## diesel:liftback-gasoline:cabriolet     -2997.01978  -6387.25898    393.219425
## electric:liftback-gasoline:cabriolet   15238.37606   -291.00528  30767.757393
## gasoline:liftback-gasoline:cabriolet   -3523.16915  -6287.71798   -758.620326
## diesel:limousine-gasoline:cabriolet             NA           NA            NA
## electric:limousine-gasoline:cabriolet           NA           NA            NA
## gasoline:limousine-gasoline:cabriolet  -3082.04061  -9842.18770   3678.106478
## diesel:minibus-gasoline:cabriolet      -2598.09656  -5239.96677     43.773646
## electric:minibus-gasoline:cabriolet             NA           NA            NA
## gasoline:minibus-gasoline:cabriolet    -4774.03089  -8083.22589  -1464.835884
## diesel:minivan-gasoline:cabriolet      -4339.52765  -6956.20497  -1722.850318
## electric:minivan-gasoline:cabriolet             NA           NA            NA
## gasoline:minivan-gasoline:cabriolet    -6012.04424  -8637.14114  -3386.947338
## diesel:pickup-gasoline:cabriolet        -532.22354  -4130.34536   3065.898287
## electric:pickup-gasoline:cabriolet              NA           NA            NA
## gasoline:pickup-gasoline:cabriolet      1917.15206  -1973.40376   5807.707871
## diesel:sedan-gasoline:cabriolet        -5122.59264  -7728.51774  -2516.667532
## electric:sedan-gasoline:cabriolet               NA           NA            NA
## gasoline:sedan-gasoline:cabriolet      -5535.39077  -8114.57214  -2956.209401
## diesel:suv-gasoline:cabriolet           3722.76912   1098.51040   6347.027838
## electric:suv-gasoline:cabriolet                 NA           NA            NA
## gasoline:suv-gasoline:cabriolet         1958.24537   -638.25538   4554.746113
## diesel:universal-gasoline:cabriolet    -5451.91247  -8053.26916  -2850.555776
## electric:universal-gasoline:cabriolet           NA           NA            NA
## gasoline:universal-gasoline:cabriolet  -7095.54711  -9701.25280  -4489.841421
## diesel:van-gasoline:cabriolet          -4293.83999  -6989.56941  -1598.110571
## electric:van-gasoline:cabriolet                 NA           NA            NA
## gasoline:van-gasoline:cabriolet        -6524.07003  -9906.87138  -3141.268670
## electric:coupe-diesel:coupe                     NA           NA            NA
## gasoline:coupe-diesel:coupe            -2795.56008  -6781.53028   1190.410117
## diesel:hatchback-diesel:coupe          -6000.69236  -9928.94321  -2072.441512
## electric:hatchback-diesel:coupe         5092.06806  -3496.94691  13681.083036
## gasoline:hatchback-diesel:coupe        -6120.44423 -10020.43093  -2220.457523
## diesel:liftback-diesel:coupe           -1881.32777  -6355.59886   2592.943319
## electric:liftback-diesel:coupe         16354.06806    552.57875  32155.557381
## gasoline:liftback-diesel:coupe         -2407.47715  -6428.43600   1613.481714
## diesel:limousine-diesel:coupe                   NA           NA            NA
## electric:limousine-diesel:coupe                 NA           NA            NA
## gasoline:limousine-diesel:coupe        -1966.34860  -9330.10909   5397.411890
## diesel:minibus-diesel:coupe            -1482.40455  -5420.02543   2455.216317
## electric:minibus-diesel:coupe                   NA           NA            NA
## gasoline:minibus-diesel:coupe          -3658.33888  -8071.51818    754.840417
## diesel:minivan-diesel:coupe            -3223.83564  -7144.59834    696.927065
## electric:minivan-diesel:coupe                   NA           NA            NA
## gasoline:minivan-diesel:coupe          -4896.35223  -8822.73908   -969.965385
## diesel:pickup-diesel:coupe               583.46847  -4050.30543   5217.242374
## electric:pickup-diesel:coupe                    NA           NA            NA
## gasoline:pickup-diesel:coupe            3032.84406  -1831.49602   7897.184150
## diesel:sedan-diesel:coupe              -4006.90063  -7920.49560    -93.305659
## electric:sedan-diesel:coupe                     NA           NA            NA
## gasoline:sedan-diesel:coupe            -4419.69876  -8315.53712   -523.860411
## diesel:suv-diesel:coupe                 4838.46113    912.63462   8764.287633
## electric:suv-diesel:coupe                       NA           NA            NA
## gasoline:suv-diesel:coupe               3073.93738   -833.38857   6981.263322
## diesel:universal-diesel:coupe          -4336.22046  -8246.77497   -425.665951
## electric:universal-diesel:coupe                 NA           NA            NA
## gasoline:universal-diesel:coupe        -5979.85510  -9893.30397  -2066.406232
## diesel:van-diesel:coupe                -3178.14798  -7152.10534    795.809369
## electric:van-diesel:coupe                       NA           NA            NA
## gasoline:van-diesel:coupe              -5408.37802  -9877.01595   -939.740089
## gasoline:coupe-electric:coupe                   NA           NA            NA
## diesel:hatchback-electric:coupe                 NA           NA            NA
## electric:hatchback-electric:coupe               NA           NA            NA
## gasoline:hatchback-electric:coupe               NA           NA            NA
## diesel:liftback-electric:coupe                  NA           NA            NA
## electric:liftback-electric:coupe                NA           NA            NA
## gasoline:liftback-electric:coupe                NA           NA            NA
## diesel:limousine-electric:coupe                 NA           NA            NA
## electric:limousine-electric:coupe               NA           NA            NA
## gasoline:limousine-electric:coupe               NA           NA            NA
## diesel:minibus-electric:coupe                   NA           NA            NA
## electric:minibus-electric:coupe                 NA           NA            NA
## gasoline:minibus-electric:coupe                 NA           NA            NA
## diesel:minivan-electric:coupe                   NA           NA            NA
## electric:minivan-electric:coupe                 NA           NA            NA
## gasoline:minivan-electric:coupe                 NA           NA            NA
## diesel:pickup-electric:coupe                    NA           NA            NA
## electric:pickup-electric:coupe                  NA           NA            NA
## gasoline:pickup-electric:coupe                  NA           NA            NA
## diesel:sedan-electric:coupe                     NA           NA            NA
## electric:sedan-electric:coupe                   NA           NA            NA
## gasoline:sedan-electric:coupe                   NA           NA            NA
## diesel:suv-electric:coupe                       NA           NA            NA
## electric:suv-electric:coupe                     NA           NA            NA
## gasoline:suv-electric:coupe                     NA           NA            NA
## diesel:universal-electric:coupe                 NA           NA            NA
## electric:universal-electric:coupe               NA           NA            NA
## gasoline:universal-electric:coupe               NA           NA            NA
## diesel:van-electric:coupe                       NA           NA            NA
## electric:van-electric:coupe                     NA           NA            NA
## gasoline:van-electric:coupe                     NA           NA            NA
## diesel:hatchback-gasoline:coupe        -3205.13228  -4231.78433  -2178.480228
## electric:hatchback-gasoline:coupe       7887.62815    180.87540  15594.380894
## gasoline:hatchback-gasoline:coupe      -3324.88414  -4237.43879  -2412.329497
## diesel:liftback-gasoline:coupe           914.23231  -1461.04903   3289.513660
## electric:liftback-gasoline:coupe       19149.62815   3809.81315  34489.443151
## gasoline:liftback-gasoline:coupe         388.08294   -950.18827   1726.354152
## diesel:limousine-gasoline:coupe                 NA           NA            NA
## electric:limousine-gasoline:coupe               NA           NA            NA
## gasoline:limousine-gasoline:coupe        829.21148  -5483.30214   7141.725107
## diesel:minibus-gasoline:coupe           1313.15553    251.21494   2375.096121
## electric:minibus-gasoline:coupe                 NA           NA            NA
## gasoline:minibus-gasoline:coupe         -862.77880  -3120.87782   1395.320227
## diesel:minivan-gasoline:coupe           -428.27555  -1425.89264    569.341537
## electric:minivan-gasoline:coupe                 NA           NA            NA
## gasoline:minivan-gasoline:coupe        -2100.79215  -3120.28877  -1081.295522
## diesel:pickup-gasoline:coupe            3379.02855    715.43694   6042.620168
## electric:pickup-gasoline:coupe                  NA           NA            NA
## gasoline:pickup-gasoline:coupe          5828.40415   2781.32946   8875.478838
## diesel:sedan-gasoline:coupe            -1211.34054  -2180.40467   -242.276422
## electric:sedan-gasoline:coupe                   NA           NA            NA
## gasoline:sedan-gasoline:coupe          -1624.13868  -2518.79849   -729.478873
## diesel:suv-gasoline:coupe               7634.02121   6616.68476   8651.357659
## electric:suv-gasoline:coupe                     NA           NA            NA
## gasoline:suv-gasoline:coupe             5869.49746   4926.06980   6812.925117
## diesel:universal-gasoline:coupe        -1540.66038  -2497.37155   -583.949207
## electric:universal-gasoline:coupe               NA           NA            NA
## gasoline:universal-gasoline:coupe      -3184.29502  -4152.76895  -2215.821084
## diesel:van-gasoline:coupe               -382.58790  -1572.20832    807.032516
## electric:van-gasoline:coupe                     NA           NA            NA
## gasoline:van-gasoline:coupe            -2612.81793  -4977.47111   -248.164759
## electric:hatchback-diesel:hatchback    11092.76043   3415.70147  18769.819380
## gasoline:hatchback-diesel:hatchback     -119.75186   -732.90134    493.397612
## diesel:liftback-diesel:hatchback        4119.36459   1842.27044   6396.458743
## electric:liftback-diesel:hatchback     22354.76043   7029.84214  37679.678717
## gasoline:liftback-diesel:hatchback      3593.21522   2438.15412   4748.276315
## diesel:limousine-diesel:hatchback               NA           NA            NA
## electric:limousine-diesel:hatchback             NA           NA            NA
## gasoline:limousine-diesel:hatchback     4034.34376  -2241.88318  10310.570698
## diesel:minibus-diesel:hatchback         4518.28781   3699.19433   5337.381282
## electric:minibus-diesel:hatchback               NA           NA            NA
## gasoline:minibus-diesel:hatchback       2342.35348    187.77522   4496.931747
## diesel:minivan-diesel:hatchback         2776.85673   2043.07463   3510.638817
## electric:minivan-diesel:hatchback               NA           NA            NA
## gasoline:minivan-diesel:hatchback       1104.34013    341.07761   1867.602647
## diesel:pickup-diesel:hatchback          6584.16083   4007.74538   9160.576285
## electric:pickup-diesel:hatchback                NA           NA            NA
## gasoline:pickup-diesel:hatchback        9033.53643   6062.36486  12004.707991
## diesel:sedan-diesel:hatchback           1993.79173   1299.32678   2688.256688
## electric:sedan-diesel:hatchback                 NA           NA            NA
## gasoline:sedan-diesel:hatchback         1580.99360    994.80893   2167.178270
## diesel:suv-diesel:hatchback            10839.15349  10078.77875  11599.528231
## electric:suv-diesel:hatchback                   NA           NA            NA
## gasoline:suv-diesel:hatchback           9074.62974   8416.41089   9732.848581
## diesel:universal-diesel:hatchback       1664.47190    987.35111   2341.592690
## electric:universal-diesel:hatchback             NA           NA            NA
## gasoline:universal-diesel:hatchback       20.83726   -672.80390    714.478422
## diesel:van-diesel:hatchback             2822.54438   1843.56888   3801.519880
## electric:van-diesel:hatchback                   NA           NA            NA
## gasoline:van-diesel:hatchback            592.31434  -1673.69116   2858.319847
## gasoline:hatchback-electric:hatchback -11212.51229 -18875.14733  -3549.877252
## diesel:liftback-electric:hatchback     -6973.39583 -14943.66441    996.872745
## electric:liftback-electric:hatchback   11262.00000  -5860.88364  28384.883637
## gasoline:liftback-electric:hatchback   -7499.54521 -15224.45230    225.361883
## diesel:limousine-electric:hatchback             NA           NA            NA
## electric:limousine-electric:hatchback           NA           NA            NA
## gasoline:limousine-electric:hatchback  -7058.41667 -16944.31814   2827.484811
## diesel:minibus-electric:hatchback      -6574.47262 -14256.33031   1107.385071
## electric:minibus-electric:hatchback             NA           NA            NA
## gasoline:minibus-electric:hatchback    -8750.40694 -16686.54145   -814.272435
## diesel:minivan-electric:hatchback      -8315.90370 -15989.13376   -642.673638
## electric:minivan-electric:hatchback             NA           NA            NA
## gasoline:minivan-electric:hatchback    -9988.42030 -17664.52563  -2312.314962
## diesel:pickup-electric:hatchback       -4508.59959 -12569.48913   3552.289937
## electric:pickup-electric:hatchback              NA           NA            NA
## gasoline:pickup-electric:hatchback     -2059.22400 -10254.82550   6136.377498
## diesel:sedan-electric:hatchback        -9098.96869 -16768.53876  -1429.398625
## electric:sedan-electric:hatchback               NA           NA            NA
## gasoline:sedan-electric:hatchback      -9511.76683 -17172.29135  -1851.242309
## diesel:suv-electric:hatchback           -253.60694  -7929.42567   7422.211794
## electric:suv-electric:hatchback                 NA           NA            NA
## gasoline:suv-electric:hatchback        -2018.13069  -9684.50372   5648.242345
## diesel:universal-electric:hatchback    -9428.28852 -17096.30756  -1760.269484
## electric:universal-electric:hatchback           NA           NA            NA
## gasoline:universal-electric:hatchback -11071.92317 -18741.41869  -3402.427649
## diesel:van-electric:hatchback          -8270.21605 -15970.76255   -569.669543
## electric:van-electric:hatchback                 NA           NA            NA
## gasoline:van-electric:hatchback       -10500.44608 -18467.55374  -2533.338428
## diesel:liftback-gasoline:hatchback      4239.11646   2011.13546   6467.097452
## electric:liftback-gasoline:hatchback   22474.51229   7156.81461  37792.209968
## gasoline:liftback-gasoline:hatchback    3712.96708   2658.02268   4767.911481
## diesel:limousine-gasoline:hatchback             NA           NA            NA
## electric:limousine-gasoline:hatchback           NA           NA            NA
## gasoline:limousine-gasoline:hatchback   4154.09562  -2104.47978  10412.671030
## diesel:minibus-gasoline:hatchback       4638.03967   3967.47598   5308.603365
## electric:minibus-gasoline:hatchback             NA           NA            NA
## gasoline:minibus-gasoline:hatchback     2462.10535    359.50005   4564.710646
## diesel:minivan-gasoline:hatchback       2896.60859   2333.42327   3459.793910
## electric:minivan-gasoline:hatchback             NA           NA            NA
## gasoline:minivan-gasoline:hatchback     1224.09199    623.00031   1825.183682
## diesel:pickup-gasoline:hatchback        6703.91270   4170.80035   9237.025037
## electric:pickup-gasoline:hatchback              NA           NA            NA
## gasoline:pickup-gasoline:hatchback      9153.28829   6219.58721  12086.989368
## diesel:sedan-gasoline:hatchback         2113.54360   1602.63938   2624.447816
## electric:sedan-gasoline:hatchback               NA           NA            NA
## gasoline:sedan-gasoline:hatchback       1700.74546   1350.95407   2050.536851
## diesel:suv-gasoline:hatchback          10958.90535  10361.48482  11556.325887
## electric:suv-gasoline:hatchback                 NA           NA            NA
## gasoline:suv-gasoline:hatchback         9194.38160   8733.95398   9654.809221
## diesel:universal-gasoline:hatchback     1784.22377   1297.15692   2271.290608
## electric:universal-gasoline:hatchback           NA           NA            NA
## gasoline:universal-gasoline:hatchback    140.58912   -369.19476    650.373009
## diesel:van-gasoline:hatchback           2942.29624   2083.73082   3800.861662
## electric:van-gasoline:hatchback                 NA           NA            NA
## gasoline:van-gasoline:hatchback          712.06621  -1504.58047   2928.712884
## electric:liftback-diesel:liftback      18235.39583   2761.51243  33709.279239
## gasoline:liftback-diesel:liftback       -526.14938  -2959.68860   1907.389852
## diesel:limousine-diesel:liftback                NA           NA            NA
## electric:limousine-diesel:liftback              NA           NA            NA
## gasoline:limousine-diesel:liftback       -85.02083  -6716.68515   6546.643483
## diesel:minibus-diesel:liftback           398.92321  -1894.29748   2692.143909
## electric:minibus-diesel:liftback                NA           NA            NA
## gasoline:minibus-diesel:liftback       -1777.01111  -4815.12805   1261.105828
## diesel:minivan-diesel:liftback         -1342.50787  -3606.65963    921.643892
## electric:minivan-diesel:liftback                NA           NA            NA
## gasoline:minivan-diesel:liftback       -3015.02446  -5288.90148   -741.147443
## diesel:pickup-diesel:liftback           2464.79624   -885.70576   5815.298235
## electric:pickup-diesel:liftback                 NA           NA            NA
## gasoline:pickup-diesel:liftback         4914.17183   1251.41229   8576.931381
## diesel:sedan-diesel:liftback           -2125.57286  -4377.28967    126.143954
## electric:sedan-diesel:liftback                  NA           NA            NA
## gasoline:sedan-diesel:liftback         -2538.37099  -4759.08248   -317.659509
## diesel:suv-diesel:liftback              6719.78890   4446.87958   8992.698218
## electric:suv-diesel:liftback                    NA           NA            NA
## gasoline:suv-diesel:liftback            4955.26514   2714.46192   7196.068367
## diesel:universal-diesel:liftback       -2454.89269  -4701.32088   -208.464505
## electric:universal-diesel:liftback              NA           NA            NA
## gasoline:universal-diesel:liftback     -4098.52733  -6349.99021  -1847.064455
## diesel:van-diesel:liftback             -1296.82021  -3651.88711   1058.246678
## electric:van-diesel:liftback                    NA           NA            NA
## gasoline:van-diesel:liftback           -3527.05025  -6645.17917   -408.921327
## gasoline:liftback-electric:liftback   -18761.54521 -34110.48902  -3412.601402
## diesel:limousine-electric:liftback              NA           NA            NA
## electric:limousine-electric:liftback            NA           NA            NA
## gasoline:limousine-electric:liftback  -18320.41667 -34862.69385  -1778.139482
## diesel:minibus-electric:liftback      -17836.47262 -33163.79541  -2509.149826
## electric:minibus-electric:liftback              NA           NA            NA
## gasoline:minibus-electric:liftback    -20012.40694 -35468.73631  -4556.077581
## diesel:minivan-electric:liftback      -19577.90370 -34900.90426  -4254.903145
## electric:minivan-electric:liftback              NA           NA            NA
## gasoline:minivan-electric:liftback    -21250.42030 -36574.86089  -5925.979702
## diesel:pickup-electric:liftback       -15770.59959 -31291.35429   -249.844894
## electric:pickup-electric:liftback               NA           NA            NA
## gasoline:pickup-electric:liftback     -13321.22400 -28912.36797   2269.919972
## diesel:sedan-electric:liftback        -20360.96869 -35682.13678  -5039.800608
## electric:sedan-electric:liftback                NA           NA            NA
## gasoline:sedan-electric:liftback      -20773.76683 -36090.40883  -5457.124822
## diesel:suv-electric:liftback          -11515.60694 -26839.90397   3808.690098
## electric:suv-electric:liftback                  NA           NA            NA
## gasoline:suv-electric:liftback        -13280.13069 -28599.69863   2039.437253
## diesel:universal-electric:liftback    -20690.28852 -36010.68024  -5369.896805
## electric:universal-electric:liftback            NA           NA            NA
## gasoline:universal-electric:liftback  -22333.92317 -37655.05393  -7012.792402
## diesel:van-electric:liftback          -19532.21605 -34868.91396  -4195.518134
## electric:van-electric:liftback                  NA           NA            NA
## gasoline:van-electric:liftback        -21762.44608 -37234.70160  -6290.190564
## diesel:limousine-gasoline:liftback              NA           NA            NA
## electric:limousine-gasoline:liftback            NA           NA            NA
## gasoline:limousine-gasoline:liftback     441.12854  -5893.53640   6775.793489
## diesel:minibus-gasoline:liftback         925.07259   -261.46419   2111.609370
## electric:minibus-gasoline:liftback              NA           NA            NA
## gasoline:minibus-gasoline:liftback     -1250.86173  -3570.16398   1068.440511
## diesel:minivan-gasoline:liftback        -816.35849  -1945.69085    312.973863
## electric:minivan-gasoline:liftback              NA           NA            NA
## gasoline:minivan-gasoline:liftback     -2488.87509  -3637.58091  -1340.169260
## diesel:pickup-gasoline:liftback         2990.94562    275.27406   5706.617170
## electric:pickup-gasoline:liftback               NA           NA            NA
## gasoline:pickup-gasoline:liftback       5440.32121   2347.61756   8533.024861
## diesel:sedan-gasoline:liftback         -1599.42348  -2703.61413   -495.232838
## electric:sedan-gasoline:liftback                NA           NA            NA
## gasoline:sedan-gasoline:liftback       -2012.22162  -3051.72529   -972.717950
## diesel:suv-gasoline:liftback            7245.93827   6099.14921   8392.727336
## electric:suv-gasoline:liftback                  NA           NA            NA
## gasoline:suv-gasoline:liftback          5481.41452   4399.65325   6563.175794
## diesel:universal-gasoline:liftback     -1928.74331  -3022.10875   -835.377882
## electric:universal-gasoline:liftback            NA           NA            NA
## gasoline:universal-gasoline:liftback   -3572.37796  -4676.05068  -2468.705239
## diesel:van-gasoline:liftback            -770.67084  -2072.72631    531.384629
## electric:van-gasoline:liftback                  NA           NA            NA
## gasoline:van-gasoline:liftback         -3000.90087  -5424.06747   -577.734278
## electric:limousine-diesel:limousine             NA           NA            NA
## gasoline:limousine-diesel:limousine             NA           NA            NA
## diesel:minibus-diesel:limousine                 NA           NA            NA
## electric:minibus-diesel:limousine               NA           NA            NA
## gasoline:minibus-diesel:limousine               NA           NA            NA
## diesel:minivan-diesel:limousine                 NA           NA            NA
## electric:minivan-diesel:limousine               NA           NA            NA
## gasoline:minivan-diesel:limousine               NA           NA            NA
## diesel:pickup-diesel:limousine                  NA           NA            NA
## electric:pickup-diesel:limousine                NA           NA            NA
## gasoline:pickup-diesel:limousine                NA           NA            NA
## diesel:sedan-diesel:limousine                   NA           NA            NA
## electric:sedan-diesel:limousine                 NA           NA            NA
## gasoline:sedan-diesel:limousine                 NA           NA            NA
## diesel:suv-diesel:limousine                     NA           NA            NA
## electric:suv-diesel:limousine                   NA           NA            NA
## gasoline:suv-diesel:limousine                   NA           NA            NA
## diesel:universal-diesel:limousine               NA           NA            NA
## electric:universal-diesel:limousine             NA           NA            NA
## gasoline:universal-diesel:limousine             NA           NA            NA
## diesel:van-diesel:limousine                     NA           NA            NA
## electric:van-diesel:limousine                   NA           NA            NA
## gasoline:van-diesel:limousine                   NA           NA            NA
## gasoline:limousine-electric:limousine           NA           NA            NA
## diesel:minibus-electric:limousine               NA           NA            NA
## electric:minibus-electric:limousine             NA           NA            NA
## gasoline:minibus-electric:limousine             NA           NA            NA
## diesel:minivan-electric:limousine               NA           NA            NA
## electric:minivan-electric:limousine             NA           NA            NA
## gasoline:minivan-electric:limousine             NA           NA            NA
## diesel:pickup-electric:limousine                NA           NA            NA
## electric:pickup-electric:limousine              NA           NA            NA
## gasoline:pickup-electric:limousine              NA           NA            NA
## diesel:sedan-electric:limousine                 NA           NA            NA
## electric:sedan-electric:limousine               NA           NA            NA
## gasoline:sedan-electric:limousine               NA           NA            NA
## diesel:suv-electric:limousine                   NA           NA            NA
## electric:suv-electric:limousine                 NA           NA            NA
## gasoline:suv-electric:limousine                 NA           NA            NA
## diesel:universal-electric:limousine             NA           NA            NA
## electric:universal-electric:limousine           NA           NA            NA
## gasoline:universal-electric:limousine           NA           NA            NA
## diesel:van-electric:limousine                   NA           NA            NA
## electric:van-electric:limousine                 NA           NA            NA
## gasoline:van-electric:limousine                 NA           NA            NA
## diesel:minibus-gasoline:limousine        483.94405  -5798.15178   6766.039873
## electric:minibus-gasoline:limousine             NA           NA            NA
## gasoline:minibus-gasoline:limousine    -1691.99028  -8282.59126   4898.610707
## diesel:minivan-gasoline:limousine      -1257.48703  -7529.02991   5014.055838
## electric:minivan-gasoline:limousine             NA           NA            NA
## gasoline:minivan-gasoline:limousine    -2930.00363  -9205.06407   3345.056809
## diesel:pickup-gasoline:limousine        2549.81707  -4190.48933   9290.123477
## electric:pickup-gasoline:limousine              NA           NA            NA
## gasoline:pickup-gasoline:limousine      4999.19267  -1901.65325  11900.038579
## diesel:sedan-gasoline:limousine        -2040.55203  -8307.61636   4226.512312
## electric:sedan-gasoline:limousine               NA           NA            NA
## gasoline:sedan-gasoline:limousine      -2453.35016  -8709.34139   3802.641072
## diesel:suv-gasoline:limousine           6804.80973    530.09989  13079.519571
## electric:suv-gasoline:limousine                 NA           NA            NA
## gasoline:suv-gasoline:limousine         5040.28598  -1222.86546  11303.437412
## diesel:universal-gasoline:limousine    -2369.87186  -8635.03797   3895.294254
## electric:universal-gasoline:limousine           NA           NA            NA
## gasoline:universal-gasoline:limousine  -4013.50650 -10280.47961   2253.466605
## diesel:van-gasoline:limousine          -1211.79938  -7516.73450   5093.135739
## electric:van-gasoline:limousine                 NA           NA            NA
## gasoline:van-gasoline:limousine        -3442.02942 -10069.89444   3185.835608
## electric:minibus-diesel:minibus                 NA           NA            NA
## gasoline:minibus-diesel:minibus        -2175.93433  -4347.54914     -4.319514
## diesel:minivan-diesel:minibus          -1741.43108  -2523.82456   -959.037609
## electric:minivan-diesel:minibus                 NA           NA            NA
## gasoline:minivan-diesel:minibus        -3413.94768  -4224.05450  -2603.840858
## diesel:pickup-diesel:minibus            2065.87302   -524.80642   4656.552468
## electric:pickup-diesel:minibus                  NA           NA            NA
## gasoline:pickup-diesel:minibus          4515.24862   1531.69975   7498.797488
## diesel:sedan-diesel:minibus            -2524.49607  -3270.14006  -1778.852083
## electric:sedan-diesel:minibus                   NA           NA            NA
## gasoline:sedan-diesel:minibus          -2937.29421  -3583.29410  -2291.294320
## diesel:suv-diesel:minibus               6320.86568   5513.47907   7128.252290
## electric:suv-diesel:minibus                     NA           NA            NA
## gasoline:suv-diesel:minibus             4556.34193   3844.33390   5268.349959
## diesel:universal-diesel:minibus        -2853.81591  -3583.33352  -2124.298291
## electric:universal-diesel:minibus               NA           NA            NA
## gasoline:universal-diesel:minibus      -4497.45055  -5242.32735  -3752.573746
## diesel:van-diesel:minibus              -1695.74343  -2711.66489   -679.821965
## electric:van-diesel:minibus                     NA           NA            NA
## gasoline:van-diesel:minibus            -3925.97346  -6208.18387  -1643.763060
## gasoline:minibus-electric:minibus               NA           NA            NA
## diesel:minivan-electric:minibus                 NA           NA            NA
## electric:minivan-electric:minibus               NA           NA            NA
## gasoline:minivan-electric:minibus               NA           NA            NA
## diesel:pickup-electric:minibus                  NA           NA            NA
## electric:pickup-electric:minibus                NA           NA            NA
## gasoline:pickup-electric:minibus                NA           NA            NA
## diesel:sedan-electric:minibus                   NA           NA            NA
## electric:sedan-electric:minibus                 NA           NA            NA
## gasoline:sedan-electric:minibus                 NA           NA            NA
## diesel:suv-electric:minibus                     NA           NA            NA
## electric:suv-electric:minibus                   NA           NA            NA
## gasoline:suv-electric:minibus                   NA           NA            NA
## diesel:universal-electric:minibus               NA           NA            NA
## electric:universal-electric:minibus             NA           NA            NA
## gasoline:universal-electric:minibus             NA           NA            NA
## diesel:van-electric:minibus                     NA           NA            NA
## electric:van-electric:minibus                   NA           NA            NA
## gasoline:van-electric:minibus                   NA           NA            NA
## diesel:minivan-gasoline:minibus          434.50324  -1706.39211   2575.398599
## electric:minivan-gasoline:minibus               NA           NA            NA
## gasoline:minivan-gasoline:minibus      -1238.01335  -3389.19127    913.164567
## diesel:pickup-gasoline:minibus          4241.80735    973.33472   7510.279984
## electric:pickup-gasoline:minibus                NA           NA            NA
## gasoline:pickup-gasoline:minibus        6691.18294   3103.30652  10279.059368
## diesel:sedan-gasoline:minibus           -348.56175  -2476.30194   1779.178448
## electric:sedan-gasoline:minibus                 NA           NA            NA
## gasoline:sedan-gasoline:minibus         -761.35988  -2856.26065   1333.540886
## diesel:suv-gasoline:minibus             8496.80001   6346.64501  10646.955005
## electric:suv-gasoline:minibus                   NA           NA            NA
## gasoline:suv-gasoline:minibus           6732.27626   4616.08893   8848.463585
## diesel:universal-gasoline:minibus       -677.88158  -2800.02421   1444.261047
## electric:universal-gasoline:minibus             NA           NA            NA
## gasoline:universal-gasoline:minibus    -2321.51622  -4448.98769   -194.044759
## diesel:van-gasoline:minibus              480.19090  -1756.63493   2717.016728
## electric:van-gasoline:minibus                   NA           NA            NA
## gasoline:van-gasoline:minibus          -1750.03914  -4779.85394   1279.775659
## electric:minivan-diesel:minivan                 NA           NA            NA
## gasoline:minivan-diesel:minivan        -1672.51660  -2396.25349   -948.779698
## diesel:pickup-diesel:minivan            3807.30411   1242.32028   6372.287930
## electric:pickup-diesel:minivan                  NA           NA            NA
## gasoline:pickup-diesel:minivan          6256.67970   3295.41546   9217.943940
## diesel:sedan-diesel:minivan             -783.06499  -1433.83914   -132.290837
## electric:sedan-diesel:minivan                   NA           NA            NA
## gasoline:sedan-diesel:minivan          -1195.86313  -1729.56519   -662.161061
## diesel:suv-diesel:minivan               8062.29676   7341.60600   8782.987526
## electric:suv-diesel:minivan                     NA           NA            NA
## gasoline:suv-diesel:minivan             6297.77301   5685.82737   6909.718657
## diesel:universal-diesel:minivan        -1112.38482  -1744.61737   -480.152280
## electric:universal-diesel:minivan               NA           NA            NA
## gasoline:universal-diesel:minivan      -2756.01947  -3405.91445  -2106.124483
## diesel:van-diesel:minivan                 45.68765   -902.79453    994.169840
## electric:van-diesel:minivan                     NA           NA            NA
## gasoline:van-diesel:minivan            -2184.54238  -4437.54180     68.457034
## gasoline:minivan-electric:minivan               NA           NA            NA
## diesel:pickup-electric:minivan                  NA           NA            NA
## electric:pickup-electric:minivan                NA           NA            NA
## gasoline:pickup-electric:minivan                NA           NA            NA
## diesel:sedan-electric:minivan                   NA           NA            NA
## electric:sedan-electric:minivan                 NA           NA            NA
## gasoline:sedan-electric:minivan                 NA           NA            NA
## diesel:suv-electric:minivan                     NA           NA            NA
## electric:suv-electric:minivan                   NA           NA            NA
## gasoline:suv-electric:minivan                   NA           NA            NA
## diesel:universal-electric:minivan               NA           NA            NA
## electric:universal-electric:minivan             NA           NA            NA
## gasoline:universal-electric:minivan             NA           NA            NA
## diesel:van-electric:minivan                     NA           NA            NA
## electric:van-electric:minivan                   NA           NA            NA
## gasoline:van-electric:minivan                   NA           NA            NA
## diesel:pickup-gasoline:minivan          5479.82070   2906.24818   8053.393224
## electric:pickup-gasoline:minivan                NA           NA            NA
## gasoline:pickup-gasoline:minivan        7929.19630   4960.48961  10897.902985
## diesel:sedan-gasoline:minivan            889.45160    205.60914   1573.294065
## electric:sedan-gasoline:minivan                 NA           NA            NA
## gasoline:sedan-gasoline:minivan          476.65347    -96.90682   1050.213759
## diesel:suv-gasoline:minivan             9734.81336   8984.12788  10485.498836
## electric:suv-gasoline:minivan                   NA           NA            NA
## gasoline:suv-gasoline:minivan           7970.28961   7323.28807   8617.291141
## diesel:universal-gasoline:minivan        560.13177   -106.09004   1226.353582
## electric:universal-gasoline:minivan             NA           NA            NA
## gasoline:universal-gasoline:minivan    -1083.50287  -1766.50873   -400.497014
## diesel:van-gasoline:minivan             1718.20425    746.73527   2689.673224
## electric:van-gasoline:minivan                   NA           NA            NA
## gasoline:van-gasoline:minivan           -512.02579  -2774.79839   1750.746822
## electric:pickup-diesel:pickup                   NA           NA            NA
## gasoline:pickup-diesel:pickup           2449.37559  -1406.60240   6305.353593
## diesel:sedan-diesel:pickup             -4590.36910  -7144.38308  -2036.355114
## electric:sedan-diesel:pickup                    NA           NA            NA
## gasoline:sedan-diesel:pickup           -5003.16723  -7529.88810  -2476.446369
## diesel:suv-diesel:pickup                4254.99266   1682.27511   6827.710210
## electric:suv-diesel:pickup                      NA           NA            NA
## gasoline:suv-diesel:pickup              2490.46891    -53.92845   5034.866261
## diesel:universal-diesel:pickup         -4919.68893  -7469.04148  -2370.336381
## electric:universal-diesel:pickup                NA           NA            NA
## gasoline:universal-diesel:pickup       -6563.32357  -9117.11368  -4009.533464
## diesel:van-diesel:pickup               -3761.61645  -6407.19746  -1116.035442
## electric:van-diesel:pickup                      NA           NA            NA
## gasoline:van-diesel:pickup             -5991.84649  -9334.82223  -2648.870748
## gasoline:pickup-electric:pickup                 NA           NA            NA
## diesel:sedan-electric:pickup                    NA           NA            NA
## electric:sedan-electric:pickup                  NA           NA            NA
## gasoline:sedan-electric:pickup                  NA           NA            NA
## diesel:suv-electric:pickup                      NA           NA            NA
## electric:suv-electric:pickup                    NA           NA            NA
## gasoline:suv-electric:pickup                    NA           NA            NA
## diesel:universal-electric:pickup                NA           NA            NA
## electric:universal-electric:pickup              NA           NA            NA
## gasoline:universal-electric:pickup              NA           NA            NA
## diesel:van-electric:pickup                      NA           NA            NA
## electric:van-electric:pickup                    NA           NA            NA
## gasoline:van-electric:pickup                    NA           NA            NA
## diesel:sedan-gasoline:pickup           -7039.74469  -9991.51218  -4087.977204
## electric:sedan-gasoline:pickup                  NA           NA            NA
## gasoline:sedan-gasoline:pickup         -7452.54283 -10380.72694  -4524.358715
## diesel:suv-gasoline:pickup              1805.61706  -1162.34848   4773.582609
## electric:suv-gasoline:pickup                    NA           NA            NA
## gasoline:suv-gasoline:pickup              41.09331  -2902.35735   2984.543970
## diesel:universal-gasoline:pickup       -7369.06452 -10316.79964  -4421.329411
## electric:universal-gasoline:pickup              NA           NA            NA
## gasoline:universal-gasoline:pickup     -9012.69917 -11964.27295  -6061.125384
## diesel:van-gasoline:pickup             -6210.99205  -9242.33544  -3179.648655
## electric:van-gasoline:pickup                    NA           NA            NA
## gasoline:van-gasoline:pickup           -8441.22208 -12097.09827  -4785.345899
## electric:sedan-diesel:sedan                     NA           NA            NA
## gasoline:sedan-diesel:sedan             -412.79814   -891.00657     65.410301
## diesel:suv-diesel:sedan                 8845.36176   8164.74396   9525.979553
## electric:suv-diesel:sedan                       NA           NA            NA
## gasoline:suv-diesel:sedan               7080.83800   6516.63690   7645.039107
## diesel:universal-diesel:sedan           -329.31983   -915.46265    256.822984
## electric:universal-diesel:sedan                 NA           NA            NA
## gasoline:universal-diesel:sedan        -1972.95448  -2578.10644  -1367.802508
## diesel:van-diesel:sedan                  828.75264    -89.65025   1747.155536
## electric:van-diesel:sedan                       NA           NA            NA
## gasoline:van-diesel:sedan              -1401.47739  -3641.97996    839.025182
## gasoline:sedan-electric:sedan                   NA           NA            NA
## diesel:suv-electric:sedan                       NA           NA            NA
## electric:suv-electric:sedan                     NA           NA            NA
## gasoline:suv-electric:sedan                     NA           NA            NA
## diesel:universal-electric:sedan                 NA           NA            NA
## electric:universal-electric:sedan               NA           NA            NA
## gasoline:universal-electric:sedan               NA           NA            NA
## diesel:van-electric:sedan                       NA           NA            NA
## electric:van-electric:sedan                     NA           NA            NA
## gasoline:van-electric:sedan                     NA           NA            NA
## diesel:suv-gasoline:sedan               9258.15989   8688.44814   9827.871646
## electric:suv-gasoline:sedan                     NA           NA            NA
## gasoline:suv-gasoline:sedan             7493.63614   7069.78029   7917.491990
## diesel:universal-gasoline:sedan           83.47830   -369.17421    536.130817
## electric:universal-gasoline:sedan               NA           NA            NA
## gasoline:universal-gasoline:sedan      -1560.15634  -2037.16766  -1083.145019
## diesel:van-gasoline:sedan               1241.55078    402.03022   2081.071339
## electric:van-gasoline:sedan                     NA           NA            NA
## gasoline:van-gasoline:sedan             -988.67925  -3198.01913   1220.660619
## electric:suv-diesel:suv                         NA           NA            NA
## gasoline:suv-diesel:suv                -1764.52375  -2408.11606  -1120.931443
## diesel:universal-diesel:suv            -9174.68159  -9837.59303  -8511.770149
## electric:universal-diesel:suv                   NA           NA            NA
## gasoline:universal-diesel:suv         -10818.31623 -11498.09346 -10138.539004
## diesel:van-diesel:suv                  -8016.60911  -8985.81087  -7047.407354
## electric:van-diesel:suv                         NA           NA            NA
## gasoline:van-diesel:suv               -10246.83915 -12508.63930  -7985.038988
## gasoline:suv-electric:suv                       NA           NA            NA
## diesel:universal-electric:suv                   NA           NA            NA
## electric:universal-electric:suv                 NA           NA            NA
## gasoline:universal-electric:suv                 NA           NA            NA
## diesel:van-electric:suv                         NA           NA            NA
## electric:van-electric:suv                       NA           NA            NA
## gasoline:van-electric:suv                       NA           NA            NA
## diesel:universal-gasoline:suv          -7410.15784  -7952.86759  -6867.448084
## electric:universal-gasoline:suv                 NA           NA            NA
## gasoline:universal-gasoline:suv        -9053.79248  -9616.97928  -8490.605675
## diesel:van-gasoline:suv                -6252.08536  -7143.39582  -5360.774894
## electric:van-gasoline:suv                       NA           NA            NA
## gasoline:van-gasoline:suv              -8482.31539 -10711.84948  -6252.781305
## electric:universal-diesel:universal             NA           NA            NA
## gasoline:universal-diesel:universal    -1643.63464  -2228.80119  -1058.468093
## diesel:van-diesel:universal             1158.07248    252.71351   2063.431444
## electric:van-diesel:universal                   NA           NA            NA
## gasoline:van-diesel:universal          -1072.15756  -3307.34497   1163.029854
## gasoline:universal-electric:universal           NA           NA            NA
## diesel:van-electric:universal                   NA           NA            NA
## electric:van-electric:universal                 NA           NA            NA
## gasoline:van-electric:universal                 NA           NA            NA
## diesel:van-gasoline:universal           2801.70712   1883.92699   3719.487247
## electric:van-gasoline:universal                 NA           NA            NA
## gasoline:van-gasoline:universal          571.47708  -1668.77028   2811.724453
## electric:van-diesel:van                         NA           NA            NA
## gasoline:van-diesel:van                -2230.23003  -4574.57712    114.117047
## gasoline:van-electric:van                       NA           NA            NA
##                                           p adj
## electric:cabriolet-diesel:cabriolet          NA
## gasoline:cabriolet-diesel:cabriolet   0.9996511
## diesel:coupe-diesel:cabriolet         0.9999996
## electric:coupe-diesel:cabriolet              NA
## gasoline:coupe-diesel:cabriolet       1.0000000
## diesel:hatchback-diesel:cabriolet     1.0000000
## electric:hatchback-diesel:cabriolet   0.8154076
## gasoline:hatchback-diesel:cabriolet   1.0000000
## diesel:liftback-diesel:cabriolet      1.0000000
## electric:liftback-diesel:cabriolet    0.0178178
## gasoline:liftback-diesel:cabriolet    1.0000000
## diesel:limousine-diesel:cabriolet            NA
## electric:limousine-diesel:cabriolet          NA
## gasoline:limousine-diesel:cabriolet   1.0000000
## diesel:minibus-diesel:cabriolet       1.0000000
## electric:minibus-diesel:cabriolet            NA
## gasoline:minibus-diesel:cabriolet     1.0000000
## diesel:minivan-diesel:cabriolet       1.0000000
## electric:minivan-diesel:cabriolet            NA
## gasoline:minivan-diesel:cabriolet     1.0000000
## diesel:pickup-diesel:cabriolet        0.9999711
## electric:pickup-diesel:cabriolet             NA
## gasoline:pickup-diesel:cabriolet      0.9321329
## diesel:sedan-diesel:cabriolet         1.0000000
## electric:sedan-diesel:cabriolet              NA
## gasoline:sedan-diesel:cabriolet       1.0000000
## diesel:suv-diesel:cabriolet           0.4292644
## electric:suv-diesel:cabriolet                NA
## gasoline:suv-diesel:cabriolet         0.8932795
## diesel:universal-diesel:cabriolet     1.0000000
## electric:universal-diesel:cabriolet          NA
## gasoline:universal-diesel:cabriolet   1.0000000
## diesel:van-diesel:cabriolet           1.0000000
## electric:van-diesel:cabriolet                NA
## gasoline:van-diesel:cabriolet         1.0000000
## gasoline:cabriolet-electric:cabriolet        NA
## diesel:coupe-electric:cabriolet              NA
## electric:coupe-electric:cabriolet            NA
## gasoline:coupe-electric:cabriolet            NA
## diesel:hatchback-electric:cabriolet          NA
## electric:hatchback-electric:cabriolet        NA
## gasoline:hatchback-electric:cabriolet        NA
## diesel:liftback-electric:cabriolet           NA
## electric:liftback-electric:cabriolet         NA
## gasoline:liftback-electric:cabriolet         NA
## diesel:limousine-electric:cabriolet          NA
## electric:limousine-electric:cabriolet        NA
## gasoline:limousine-electric:cabriolet        NA
## diesel:minibus-electric:cabriolet            NA
## electric:minibus-electric:cabriolet          NA
## gasoline:minibus-electric:cabriolet          NA
## diesel:minivan-electric:cabriolet            NA
## electric:minivan-electric:cabriolet          NA
## gasoline:minivan-electric:cabriolet          NA
## diesel:pickup-electric:cabriolet             NA
## electric:pickup-electric:cabriolet           NA
## gasoline:pickup-electric:cabriolet           NA
## diesel:sedan-electric:cabriolet              NA
## electric:sedan-electric:cabriolet            NA
## gasoline:sedan-electric:cabriolet            NA
## diesel:suv-electric:cabriolet                NA
## electric:suv-electric:cabriolet              NA
## gasoline:suv-electric:cabriolet              NA
## diesel:universal-electric:cabriolet          NA
## electric:universal-electric:cabriolet        NA
## gasoline:universal-electric:cabriolet        NA
## diesel:van-electric:cabriolet                NA
## electric:van-electric:cabriolet              NA
## gasoline:van-electric:cabriolet              NA
## diesel:coupe-gasoline:cabriolet       1.0000000
## electric:coupe-gasoline:cabriolet            NA
## gasoline:coupe-gasoline:cabriolet     0.0000194
## diesel:hatchback-gasoline:cabriolet   0.0000000
## electric:hatchback-gasoline:cabriolet 0.9968849
## gasoline:hatchback-gasoline:cabriolet 0.0000000
## diesel:liftback-gasoline:cabriolet    0.1957844
## electric:liftback-gasoline:cabriolet  0.0638644
## gasoline:liftback-gasoline:cabriolet  0.0005776
## diesel:limousine-gasoline:cabriolet          NA
## electric:limousine-gasoline:cabriolet        NA
## gasoline:limousine-gasoline:cabriolet 0.9992550
## diesel:minibus-gasoline:cabriolet     0.0621080
## electric:minibus-gasoline:cabriolet          NA
## gasoline:minibus-gasoline:cabriolet   0.0000189
## diesel:minivan-gasoline:cabriolet     0.0000001
## electric:minivan-gasoline:cabriolet          NA
## gasoline:minivan-gasoline:cabriolet   0.0000000
## diesel:pickup-gasoline:cabriolet      1.0000000
## electric:pickup-gasoline:cabriolet           NA
## gasoline:pickup-gasoline:cabriolet    0.9968296
## diesel:sedan-gasoline:cabriolet       0.0000000
## electric:sedan-gasoline:cabriolet            NA
## gasoline:sedan-gasoline:cabriolet     0.0000000
## diesel:suv-gasoline:cabriolet         0.0000318
## electric:suv-gasoline:cabriolet              NA
## gasoline:suv-gasoline:cabriolet       0.5575133
## diesel:universal-gasoline:cabriolet   0.0000000
## electric:universal-gasoline:cabriolet        NA
## gasoline:universal-gasoline:cabriolet 0.0000000
## diesel:van-gasoline:cabriolet         0.0000006
## electric:van-gasoline:cabriolet              NA
## gasoline:van-gasoline:cabriolet       0.0000000
## electric:coupe-diesel:coupe                  NA
## gasoline:coupe-diesel:coupe           0.7250355
## diesel:hatchback-diesel:coupe         0.0000028
## electric:hatchback-diesel:coupe       0.9485097
## gasoline:hatchback-diesel:coupe       0.0000011
## diesel:liftback-diesel:coupe          0.9998589
## electric:liftback-diesel:coupe        0.0309514
## gasoline:liftback-diesel:coupe        0.9418794
## diesel:limousine-diesel:coupe                NA
## electric:limousine-diesel:coupe              NA
## gasoline:limousine-diesel:coupe       1.0000000
## diesel:minibus-diesel:coupe           0.9999885
## electric:minibus-diesel:coupe                NA
## gasoline:minibus-diesel:coupe         0.3264607
## diesel:minivan-diesel:coupe           0.3451627
## electric:minivan-diesel:coupe                NA
## gasoline:minivan-diesel:coupe         0.0009626
## diesel:pickup-diesel:coupe            1.0000000
## electric:pickup-diesel:coupe                 NA
## gasoline:pickup-diesel:coupe          0.9072200
## diesel:sedan-diesel:coupe             0.0361690
## electric:sedan-diesel:coupe                  NA
## gasoline:sedan-diesel:coupe           0.0068017
## diesel:suv-diesel:coupe               0.0012564
## electric:suv-diesel:coupe                    NA
## gasoline:suv-diesel:coupe             0.4521546
## diesel:universal-diesel:coupe         0.0102522
## electric:universal-diesel:coupe              NA
## gasoline:universal-diesel:coupe       0.0000028
## diesel:van-diesel:coupe               0.4115505
## electric:van-diesel:coupe                    NA
## gasoline:van-diesel:coupe             0.0018706
## gasoline:coupe-electric:coupe                NA
## diesel:hatchback-electric:coupe              NA
## electric:hatchback-electric:coupe            NA
## gasoline:hatchback-electric:coupe            NA
## diesel:liftback-electric:coupe               NA
## electric:liftback-electric:coupe             NA
## gasoline:liftback-electric:coupe             NA
## diesel:limousine-electric:coupe              NA
## electric:limousine-electric:coupe            NA
## gasoline:limousine-electric:coupe            NA
## diesel:minibus-electric:coupe                NA
## electric:minibus-electric:coupe              NA
## gasoline:minibus-electric:coupe              NA
## diesel:minivan-electric:coupe                NA
## electric:minivan-electric:coupe              NA
## gasoline:minivan-electric:coupe              NA
## diesel:pickup-electric:coupe                 NA
## electric:pickup-electric:coupe               NA
## gasoline:pickup-electric:coupe               NA
## diesel:sedan-electric:coupe                  NA
## electric:sedan-electric:coupe                NA
## gasoline:sedan-electric:coupe                NA
## diesel:suv-electric:coupe                    NA
## electric:suv-electric:coupe                  NA
## gasoline:suv-electric:coupe                  NA
## diesel:universal-electric:coupe              NA
## electric:universal-electric:coupe            NA
## gasoline:universal-electric:coupe            NA
## diesel:van-electric:coupe                    NA
## electric:van-electric:coupe                  NA
## gasoline:van-electric:coupe                  NA
## diesel:hatchback-gasoline:coupe       0.0000000
## electric:hatchback-gasoline:coupe     0.0363558
## gasoline:hatchback-gasoline:coupe     0.0000000
## diesel:liftback-gasoline:coupe        0.9999806
## electric:liftback-gasoline:coupe      0.0009394
## gasoline:liftback-gasoline:coupe      1.0000000
## diesel:limousine-gasoline:coupe              NA
## electric:limousine-gasoline:coupe            NA
## gasoline:limousine-gasoline:coupe     1.0000000
## diesel:minibus-gasoline:coupe         0.0011662
## electric:minibus-gasoline:coupe              NA
## gasoline:minibus-gasoline:coupe       0.9999837
## diesel:minivan-gasoline:coupe         0.9997806
## electric:minivan-gasoline:coupe              NA
## gasoline:minivan-gasoline:coupe       0.0000000
## diesel:pickup-gasoline:coupe          0.0006444
## electric:pickup-gasoline:coupe               NA
## gasoline:pickup-gasoline:coupe        0.0000000
## diesel:sedan-gasoline:coupe           0.0009112
## electric:sedan-gasoline:coupe                NA
## gasoline:sedan-gasoline:coupe         0.0000000
## diesel:suv-gasoline:coupe             0.0000000
## electric:suv-gasoline:coupe                  NA
## gasoline:suv-gasoline:coupe           0.0000000
## diesel:universal-gasoline:coupe       0.0000004
## electric:universal-gasoline:coupe            NA
## gasoline:universal-gasoline:coupe     0.0000000
## diesel:van-gasoline:coupe             0.9999998
## electric:van-gasoline:coupe                  NA
## gasoline:van-gasoline:coupe           0.0109006
## electric:hatchback-diesel:hatchback   0.0000180
## gasoline:hatchback-diesel:hatchback   1.0000000
## diesel:liftback-diesel:hatchback      0.0000000
## electric:liftback-diesel:hatchback    0.0000133
## gasoline:liftback-diesel:hatchback    0.0000000
## diesel:limousine-diesel:hatchback            NA
## electric:limousine-diesel:hatchback          NA
## gasoline:limousine-diesel:hatchback   0.8721900
## diesel:minibus-diesel:hatchback       0.0000000
## electric:minibus-diesel:hatchback            NA
## gasoline:minibus-diesel:hatchback     0.0143589
## diesel:minivan-diesel:hatchback       0.0000000
## electric:minivan-diesel:hatchback            NA
## gasoline:minivan-diesel:hatchback     0.0000173
## diesel:pickup-diesel:hatchback        0.0000000
## electric:pickup-diesel:hatchback             NA
## gasoline:pickup-diesel:hatchback      0.0000000
## diesel:sedan-diesel:hatchback         0.0000000
## electric:sedan-diesel:hatchback              NA
## gasoline:sedan-diesel:hatchback       0.0000000
## diesel:suv-diesel:hatchback           0.0000000
## electric:suv-diesel:hatchback                NA
## gasoline:suv-diesel:hatchback         0.0000000
## diesel:universal-diesel:hatchback     0.0000000
## electric:universal-diesel:hatchback          NA
## gasoline:universal-diesel:hatchback   1.0000000
## diesel:van-diesel:hatchback           0.0000000
## electric:van-diesel:hatchback                NA
## gasoline:van-diesel:hatchback         1.0000000
## gasoline:hatchback-electric:hatchback 0.0000121
## diesel:liftback-electric:hatchback    0.2144133
## electric:liftback-electric:hatchback  0.8402707
## gasoline:liftback-electric:hatchback  0.0729080
## diesel:limousine-electric:hatchback          NA
## electric:limousine-electric:hatchback        NA
## gasoline:limousine-electric:hatchback 0.6867809
## diesel:minibus-electric:hatchback     0.2573685
## electric:minibus-electric:hatchback          NA
## gasoline:minibus-electric:hatchback   0.0113079
## diesel:minivan-electric:hatchback     0.0151226
## electric:minivan-electric:hatchback          NA
## gasoline:minivan-electric:hatchback   0.0003457
## diesel:pickup-electric:hatchback      0.9762396
## electric:pickup-electric:hatchback           NA
## gasoline:pickup-electric:hatchback    1.0000000
## diesel:sedan-electric:hatchback       0.0028448
## electric:sedan-electric:hatchback            NA
## gasoline:sedan-electric:hatchback     0.0010625
## diesel:suv-electric:hatchback         1.0000000
## electric:suv-electric:hatchback              NA
## gasoline:suv-electric:hatchback       1.0000000
## diesel:universal-electric:hatchback   0.0013244
## electric:universal-electric:hatchback        NA
## gasoline:universal-electric:hatchback 0.0000185
## diesel:van-electric:hatchback         0.0175310
## electric:van-electric:hatchback              NA
## gasoline:van-electric:hatchback       0.0002494
## diesel:liftback-gasoline:hatchback    0.0000000
## electric:liftback-gasoline:hatchback  0.0000111
## gasoline:liftback-gasoline:hatchback  0.0000000
## diesel:limousine-gasoline:hatchback          NA
## electric:limousine-gasoline:hatchback        NA
## gasoline:limousine-gasoline:hatchback 0.8262069
## diesel:minibus-gasoline:hatchback     0.0000000
## electric:minibus-gasoline:hatchback          NA
## gasoline:minibus-gasoline:hatchback   0.0037043
## diesel:minivan-gasoline:hatchback     0.0000000
## electric:minivan-gasoline:hatchback          NA
## gasoline:minivan-gasoline:hatchback   0.0000000
## diesel:pickup-gasoline:hatchback      0.0000000
## electric:pickup-gasoline:hatchback           NA
## gasoline:pickup-gasoline:hatchback    0.0000000
## diesel:sedan-gasoline:hatchback       0.0000000
## electric:sedan-gasoline:hatchback            NA
## gasoline:sedan-gasoline:hatchback     0.0000000
## diesel:suv-gasoline:hatchback         0.0000000
## electric:suv-gasoline:hatchback              NA
## gasoline:suv-gasoline:hatchback       0.0000000
## diesel:universal-gasoline:hatchback   0.0000000
## electric:universal-gasoline:hatchback        NA
## gasoline:universal-gasoline:hatchback 1.0000000
## diesel:van-gasoline:hatchback         0.0000000
## electric:van-gasoline:hatchback              NA
## gasoline:van-gasoline:hatchback       0.9999998
## electric:liftback-diesel:liftback     0.0032599
## gasoline:liftback-diesel:liftback     1.0000000
## diesel:limousine-diesel:liftback             NA
## electric:limousine-diesel:liftback           NA
## gasoline:limousine-diesel:liftback    1.0000000
## diesel:minibus-diesel:liftback        1.0000000
## electric:minibus-diesel:liftback             NA
## gasoline:minibus-diesel:liftback      0.9565832
## diesel:minivan-diesel:liftback        0.9484205
## electric:minivan-diesel:liftback             NA
## gasoline:minivan-diesel:liftback      0.0002131
## diesel:pickup-diesel:liftback         0.6180313
## electric:pickup-diesel:liftback              NA
## gasoline:pickup-diesel:liftback       0.0001558
## diesel:sedan-diesel:liftback          0.1011808
## electric:sedan-diesel:liftback               NA
## gasoline:sedan-diesel:liftback        0.0059109
## diesel:suv-diesel:liftback            0.0000000
## electric:suv-diesel:liftback                 NA
## gasoline:suv-diesel:liftback          0.0000000
## diesel:universal-diesel:liftback      0.0131664
## electric:universal-diesel:liftback           NA
## gasoline:universal-diesel:liftback    0.0000000
## diesel:van-diesel:liftback            0.9810090
## electric:van-diesel:liftback                 NA
## gasoline:van-diesel:liftback          0.0071790
## gasoline:liftback-electric:liftback   0.0015088
## diesel:limousine-electric:liftback           NA
## electric:limousine-electric:liftback         NA
## gasoline:limousine-electric:liftback  0.0104740
## diesel:minibus-electric:liftback      0.0041898
## electric:minibus-electric:liftback           NA
## gasoline:minibus-electric:liftback    0.0003917
## diesel:minivan-electric:liftback      0.0005429
## electric:minivan-electric:liftback           NA
## gasoline:minivan-electric:liftback    0.0000621
## diesel:pickup-electric:liftback       0.0402408
## electric:pickup-electric:liftback            NA
## gasoline:pickup-electric:liftback     0.2608062
## diesel:sedan-electric:liftback        0.0002008
## electric:sedan-electric:liftback             NA
## gasoline:sedan-electric:liftback      0.0001160
## diesel:suv-electric:liftback          0.5664469
## electric:suv-electric:liftback               NA
## gasoline:suv-electric:liftback        0.2319068
## diesel:universal-electric:liftback    0.0001304
## electric:universal-electric:liftback         NA
## gasoline:universal-electric:liftback  0.0000136
## diesel:van-electric:liftback          0.0005869
## electric:van-electric:liftback               NA
## gasoline:van-electric:liftback        0.0000410
## diesel:limousine-gasoline:liftback           NA
## electric:limousine-gasoline:liftback         NA
## gasoline:limousine-gasoline:liftback  1.0000000
## diesel:minibus-gasoline:liftback      0.4746845
## electric:minibus-gasoline:liftback           NA
## gasoline:minibus-gasoline:liftback    0.9860558
## diesel:minivan-gasoline:liftback      0.6589921
## electric:minivan-gasoline:liftback           NA
## gasoline:minivan-gasoline:liftback    0.0000000
## diesel:pickup-gasoline:liftback       0.0115286
## electric:pickup-gasoline:liftback            NA
## gasoline:pickup-gasoline:liftback     0.0000000
## diesel:sedan-gasoline:liftback        0.0000167
## electric:sedan-gasoline:liftback             NA
## gasoline:sedan-gasoline:liftback      0.0000000
## diesel:suv-gasoline:liftback          0.0000000
## electric:suv-gasoline:liftback               NA
## gasoline:suv-gasoline:liftback        0.0000000
## diesel:universal-gasoline:liftback    0.0000000
## electric:universal-gasoline:liftback         NA
## gasoline:universal-gasoline:liftback  0.0000000
## diesel:van-gasoline:liftback          0.9495495
## electric:van-gasoline:liftback               NA
## gasoline:van-gasoline:liftback        0.0011274
## electric:limousine-diesel:limousine          NA
## gasoline:limousine-diesel:limousine          NA
## diesel:minibus-diesel:limousine              NA
## electric:minibus-diesel:limousine            NA
## gasoline:minibus-diesel:limousine            NA
## diesel:minivan-diesel:limousine              NA
## electric:minivan-diesel:limousine            NA
## gasoline:minivan-diesel:limousine            NA
## diesel:pickup-diesel:limousine               NA
## electric:pickup-diesel:limousine             NA
## gasoline:pickup-diesel:limousine             NA
## diesel:sedan-diesel:limousine                NA
## electric:sedan-diesel:limousine              NA
## gasoline:sedan-diesel:limousine              NA
## diesel:suv-diesel:limousine                  NA
## electric:suv-diesel:limousine                NA
## gasoline:suv-diesel:limousine                NA
## diesel:universal-diesel:limousine            NA
## electric:universal-diesel:limousine          NA
## gasoline:universal-diesel:limousine          NA
## diesel:van-diesel:limousine                  NA
## electric:van-diesel:limousine                NA
## gasoline:van-diesel:limousine                NA
## gasoline:limousine-electric:limousine        NA
## diesel:minibus-electric:limousine            NA
## electric:minibus-electric:limousine          NA
## gasoline:minibus-electric:limousine          NA
## diesel:minivan-electric:limousine            NA
## electric:minivan-electric:limousine          NA
## gasoline:minivan-electric:limousine          NA
## diesel:pickup-electric:limousine             NA
## electric:pickup-electric:limousine           NA
## gasoline:pickup-electric:limousine           NA
## diesel:sedan-electric:limousine              NA
## electric:sedan-electric:limousine            NA
## gasoline:sedan-electric:limousine            NA
## diesel:suv-electric:limousine                NA
## electric:suv-electric:limousine              NA
## gasoline:suv-electric:limousine              NA
## diesel:universal-electric:limousine          NA
## electric:universal-electric:limousine        NA
## gasoline:universal-electric:limousine        NA
## diesel:van-electric:limousine                NA
## electric:van-electric:limousine              NA
## gasoline:van-electric:limousine              NA
## diesel:minibus-gasoline:limousine     1.0000000
## electric:minibus-gasoline:limousine          NA
## gasoline:minibus-gasoline:limousine   1.0000000
## diesel:minivan-gasoline:limousine     1.0000000
## electric:minivan-gasoline:limousine          NA
## gasoline:minivan-gasoline:limousine   0.9988186
## diesel:pickup-gasoline:limousine      0.9999871
## electric:pickup-gasoline:limousine           NA
## gasoline:pickup-gasoline:limousine    0.6540351
## diesel:sedan-gasoline:limousine       0.9999997
## electric:sedan-gasoline:limousine            NA
## gasoline:sedan-gasoline:limousine     0.9999701
## diesel:suv-gasoline:limousine         0.0149561
## electric:suv-gasoline:limousine              NA
## gasoline:suv-gasoline:limousine       0.3963283
## diesel:universal-gasoline:limousine   0.9999871
## electric:universal-gasoline:limousine        NA
## gasoline:universal-gasoline:limousine 0.8768847
## diesel:van-gasoline:limousine         1.0000000
## electric:van-gasoline:limousine              NA
## gasoline:van-gasoline:limousine       0.9922921
## electric:minibus-diesel:minibus              NA
## gasoline:minibus-diesel:minibus       0.0486929
## diesel:minivan-diesel:minibus         0.0000000
## electric:minivan-diesel:minibus              NA
## gasoline:minivan-diesel:minibus       0.0000000
## diesel:pickup-diesel:minibus          0.4186742
## electric:pickup-diesel:minibus               NA
## gasoline:pickup-diesel:minibus        0.0000039
## diesel:sedan-diesel:minibus           0.0000000
## electric:sedan-diesel:minibus                NA
## gasoline:sedan-diesel:minibus         0.0000000
## diesel:suv-diesel:minibus             0.0000000
## electric:suv-diesel:minibus                  NA
## gasoline:suv-diesel:minibus           0.0000000
## diesel:universal-diesel:minibus       0.0000000
## electric:universal-diesel:minibus            NA
## gasoline:universal-diesel:minibus     0.0000000
## diesel:van-diesel:minibus             0.0000001
## electric:van-diesel:minibus                  NA
## gasoline:van-diesel:minibus           0.0000000
## gasoline:minibus-electric:minibus            NA
## diesel:minivan-electric:minibus              NA
## electric:minivan-electric:minibus            NA
## gasoline:minivan-electric:minibus            NA
## diesel:pickup-electric:minibus               NA
## electric:pickup-electric:minibus             NA
## gasoline:pickup-electric:minibus             NA
## diesel:sedan-electric:minibus                NA
## electric:sedan-electric:minibus              NA
## gasoline:sedan-electric:minibus              NA
## diesel:suv-electric:minibus                  NA
## electric:suv-electric:minibus                NA
## gasoline:suv-electric:minibus                NA
## diesel:universal-electric:minibus            NA
## electric:universal-electric:minibus          NA
## gasoline:universal-electric:minibus          NA
## diesel:van-electric:minibus                  NA
## electric:van-electric:minibus                NA
## gasoline:van-electric:minibus                NA
## diesel:minivan-gasoline:minibus       1.0000000
## electric:minivan-gasoline:minibus            NA
## gasoline:minivan-gasoline:minibus     0.9648647
## diesel:pickup-gasoline:minibus        0.0003695
## electric:pickup-gasoline:minibus             NA
## gasoline:pickup-gasoline:minibus      0.0000000
## diesel:sedan-gasoline:minibus         1.0000000
## electric:sedan-gasoline:minibus              NA
## gasoline:sedan-gasoline:minibus       0.9999951
## diesel:suv-gasoline:minibus           0.0000000
## electric:suv-gasoline:minibus                NA
## gasoline:suv-gasoline:minibus         0.0000000
## diesel:universal-gasoline:minibus     0.9999998
## electric:universal-gasoline:minibus          NA
## gasoline:universal-gasoline:minibus   0.0134925
## diesel:van-gasoline:minibus           1.0000000
## electric:van-gasoline:minibus                NA
## gasoline:van-gasoline:minibus         0.9631272
## electric:minivan-diesel:minivan              NA
## gasoline:minivan-diesel:minivan       0.0000000
## diesel:pickup-diesel:minivan          0.0000076
## electric:pickup-diesel:minivan               NA
## gasoline:pickup-diesel:minivan        0.0000000
## diesel:sedan-diesel:minivan           0.0021176
## electric:sedan-diesel:minivan                NA
## gasoline:sedan-diesel:minivan         0.0000000
## diesel:suv-diesel:minivan             0.0000000
## electric:suv-diesel:minivan                  NA
## gasoline:suv-diesel:minivan           0.0000000
## diesel:universal-diesel:minivan       0.0000000
## electric:universal-diesel:minivan            NA
## gasoline:universal-diesel:minivan     0.0000000
## diesel:van-diesel:minivan             1.0000000
## electric:van-diesel:minivan                  NA
## gasoline:van-diesel:minivan           0.0740243
## gasoline:minivan-electric:minivan            NA
## diesel:pickup-electric:minivan               NA
## electric:pickup-electric:minivan             NA
## gasoline:pickup-electric:minivan             NA
## diesel:sedan-electric:minivan                NA
## electric:sedan-electric:minivan              NA
## gasoline:sedan-electric:minivan              NA
## diesel:suv-electric:minivan                  NA
## electric:suv-electric:minivan                NA
## gasoline:suv-electric:minivan                NA
## diesel:universal-electric:minivan            NA
## electric:universal-electric:minivan          NA
## gasoline:universal-electric:minivan          NA
## diesel:van-electric:minivan                  NA
## electric:van-electric:minivan                NA
## gasoline:van-electric:minivan                NA
## diesel:pickup-gasoline:minivan        0.0000000
## electric:pickup-gasoline:minivan             NA
## gasoline:pickup-gasoline:minivan      0.0000000
## diesel:sedan-gasoline:minivan         0.0003495
## electric:sedan-gasoline:minivan              NA
## gasoline:sedan-gasoline:minivan       0.3207608
## diesel:suv-gasoline:minivan           0.0000000
## electric:suv-gasoline:minivan                NA
## gasoline:suv-gasoline:minivan         0.0000000
## diesel:universal-gasoline:minivan     0.2949449
## electric:universal-gasoline:minivan          NA
## gasoline:universal-gasoline:minivan   0.0000007
## diesel:van-gasoline:minivan           0.0000000
## electric:van-gasoline:minivan                NA
## gasoline:van-gasoline:minivan         1.0000000
## electric:pickup-diesel:pickup                NA
## gasoline:pickup-diesel:pickup         0.8867955
## diesel:sedan-diesel:pickup            0.0000000
## electric:sedan-diesel:pickup                 NA
## gasoline:sedan-diesel:pickup          0.0000000
## diesel:suv-diesel:pickup              0.0000001
## electric:suv-diesel:pickup                   NA
## gasoline:suv-diesel:pickup            0.0659031
## diesel:universal-diesel:pickup        0.0000000
## electric:universal-diesel:pickup             NA
## gasoline:universal-diesel:pickup      0.0000000
## diesel:van-diesel:pickup              0.0000296
## electric:van-diesel:pickup                   NA
## gasoline:van-diesel:pickup            0.0000000
## gasoline:pickup-electric:pickup              NA
## diesel:sedan-electric:pickup                 NA
## electric:sedan-electric:pickup               NA
## gasoline:sedan-electric:pickup               NA
## diesel:suv-electric:pickup                   NA
## electric:suv-electric:pickup                 NA
## gasoline:suv-electric:pickup                 NA
## diesel:universal-electric:pickup             NA
## electric:universal-electric:pickup           NA
## gasoline:universal-electric:pickup           NA
## diesel:van-electric:pickup                   NA
## electric:van-electric:pickup                 NA
## gasoline:van-electric:pickup                 NA
## diesel:sedan-gasoline:pickup          0.0000000
## electric:sedan-gasoline:pickup               NA
## gasoline:sedan-gasoline:pickup        0.0000000
## diesel:suv-gasoline:pickup            0.9297101
## electric:suv-gasoline:pickup                 NA
## gasoline:suv-gasoline:pickup          1.0000000
## diesel:universal-gasoline:pickup      0.0000000
## electric:universal-gasoline:pickup           NA
## gasoline:universal-gasoline:pickup    0.0000000
## diesel:van-gasoline:pickup            0.0000000
## electric:van-gasoline:pickup                 NA
## gasoline:van-gasoline:pickup          0.0000000
## electric:sedan-diesel:sedan                  NA
## gasoline:sedan-diesel:sedan           0.2401545
## diesel:suv-diesel:sedan               0.0000000
## electric:suv-diesel:sedan                    NA
## gasoline:suv-diesel:sedan             0.0000000
## diesel:universal-diesel:sedan         0.9746867
## electric:universal-diesel:sedan              NA
## gasoline:universal-diesel:sedan       0.0000000
## diesel:van-diesel:sedan               0.1617026
## electric:van-diesel:sedan                    NA
## gasoline:van-diesel:sedan             0.9038666
## gasoline:sedan-electric:sedan                NA
## diesel:suv-electric:sedan                    NA
## electric:suv-electric:sedan                  NA
## gasoline:suv-electric:sedan                  NA
## diesel:universal-electric:sedan              NA
## electric:universal-electric:sedan            NA
## gasoline:universal-electric:sedan            NA
## diesel:van-electric:sedan                    NA
## electric:van-electric:sedan                  NA
## gasoline:van-electric:sedan                  NA
## diesel:suv-gasoline:sedan             0.0000000
## electric:suv-gasoline:sedan                  NA
## gasoline:suv-gasoline:sedan           0.0000000
## diesel:universal-gasoline:sedan       1.0000000
## electric:universal-gasoline:sedan            NA
## gasoline:universal-gasoline:sedan     0.0000000
## diesel:van-gasoline:sedan             0.0000085
## electric:van-gasoline:sedan                  NA
## gasoline:van-gasoline:sedan           0.9994851
## electric:suv-diesel:suv                      NA
## gasoline:suv-diesel:suv               0.0000000
## diesel:universal-diesel:suv           0.0000000
## electric:universal-diesel:suv                NA
## gasoline:universal-diesel:suv         0.0000000
## diesel:van-diesel:suv                 0.0000000
## electric:van-diesel:suv                      NA
## gasoline:van-diesel:suv               0.0000000
## gasoline:suv-electric:suv                    NA
## diesel:universal-electric:suv                NA
## electric:universal-electric:suv              NA
## gasoline:universal-electric:suv              NA
## diesel:van-electric:suv                      NA
## electric:van-electric:suv                    NA
## gasoline:van-electric:suv                    NA
## diesel:universal-gasoline:suv         0.0000000
## electric:universal-gasoline:suv              NA
## gasoline:universal-gasoline:suv       0.0000000
## diesel:van-gasoline:suv               0.0000000
## electric:van-gasoline:suv                    NA
## gasoline:van-gasoline:suv             0.0000000
## electric:universal-diesel:universal          NA
## gasoline:universal-diesel:universal   0.0000000
## diesel:van-diesel:universal           0.0005282
## electric:van-diesel:universal                NA
## gasoline:van-diesel:universal         0.9980468
## gasoline:universal-electric:universal        NA
## diesel:van-electric:universal                NA
## electric:van-electric:universal              NA
## gasoline:van-electric:universal              NA
## diesel:van-gasoline:universal         0.0000000
## electric:van-gasoline:universal              NA
## gasoline:van-gasoline:universal       1.0000000
## electric:van-diesel:van                      NA
## gasoline:van-diesel:van               0.0926816
## gasoline:van-electric:van                    NA

The Tukey Test results can be evaluated to gain more detailed information on the relationship between price and Engine/Body Type.

These tests confirm our that Engine Type and Body Type significantly impact the selling price of a vehicle.

Q8: What is the average age of each vehicle manufacturer and whether the manufacturer changes how the production year impacts the price?

A: The average age of each manufacturer can be found using some data transformation. Furthermore, the manufacturer does influence how production year changes the price of a vehicle.

Justification:

Prior to working on this question it would be useful to have some sort of visual understanding of our data. To accomplish this we will use a scatter plat with facet wrap to show the distribution of years for each manufacturer.

#Scatter plot: Year produced by price and colored by manufacturer name
ggplot(cars_edited, aes(x = year_produced, y = price_usd)) + geom_hex() + facet_wrap(~ manufacturer_name)

Upon looking

#Group cars by manufacturer name
manufacturer_year <- group_by(cars_edited, manufacturer_name)

#Summarize the manufacturer years average
manufacturer_year_averages <- summarise(manufacturer_year, average = mean(year_produced, na.rm = TRUE))
# 1) Average age of each vehicle manufacturer
manufacturer_year_averages
## # A tibble: 55 x 2
##    manufacturer_name average
##    <chr>               <dbl>
##  1 Acura               2007.
##  2 Alfa Romeo          1999.
##  3 Audi                2000.
##  4 AvtoVAZ             1994.
##  5 BMW                 2003.
##  6 Buick               2014.
##  7 Cadillac            2006 
##  8 Chery               2011.
##  9 Chevrolet           2011.
## 10 Chrysler            2002.
## # … with 45 more rows

With this question we decided to use a scatter plot and color all the points in the scatter plot with a color corresponding to a different manufacturer.

Again we can’t look at just the graph and call it a day, we need to confirm the results using a different method.

manufacturer_price <- aov(price_usd ~ manufacturer_name * year_produced, data = cars_edited)
summary(manufacturer_price)
##                                    Df    Sum Sq   Mean Sq F value Pr(>F)    
## manufacturer_name                  54 2.917e+11 5.402e+09   428.4 <2e-16 ***
## year_produced                       1 6.854e+11 6.854e+11 54355.5 <2e-16 ***
## manufacturer_name:year_produced    54 1.273e+11 2.357e+09   186.9 <2e-16 ***
## Residuals                       38380 4.840e+11 1.261e+07                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

With these results we can confirm our original assumption. The manufacturer does change how the production year affects the selling price.

Answer the goal here: In an attempt to create the most accurate and significant predictive model we created 6 different models which had a wide range of accuracy.

Model Results and Comparisons

Linear Regression Model

Firstly, we created a Multiple Linear Regression Model which utilized the attributes in our dataset that had continuous data. The code for this looks as follows:

LMCont <- lm(price_usd ~ odometer_value
             + year_produced
             + number_of_photos
             + duration_listed
             + up_counter
             , data = train.data)

step.LMConts <- LMCont %>% stepAIC(trace = FALSE)

Now that the model is created it is vital to check the accuracy of the model. To do this we will employed our test.data to test how accurately the Linear Regression model can predict the price of a vehicle.

# Predict using Multiple Linear Regression Model
LMContPrediction <- predict(step.LMConts, test.data)

# Prediction error, rmse
RMSE(LMContPrediction,test.data$price_usd) # RMSE is 4573.511
## [1] 4573.511
# Compute R-square
R2(LMContPrediction,test.data$price_usd) ## R^2 for test/train is 50.95891%
## [1] 0.5095891

From the code above we see that our rmse is 4573.511 which represents an error rate of 4573.511/mean(test.data$price_usd) = 68.60393 which is not good at all. Meanwhile, the R2 is 0.5095891, meaning that the observed and predicted outcome values are not very correlated, which is not good. These results are not surprising whatsoever and merely inform us that the price of a vehicle in Belarus is dependent on more attributes than simply our continuous attributes. We shall proceed with more robust models in order to achieve a better result.

After doing the Linear Regression Model we attempted to use SVR in order to create a more robust predictive model.

SVR Model

SVR is an extremely robust model which would be able to handle our categorical data and almost certainly achieve a better result that the Linear Regression Model. 3 SVR models were calculated were varying accuracies. The different methods used with SVR were linear, polynomial, and radial. Linear was the first SVR model to be run and the code was as follows:

# Create SVR Model using Linear Method
modelSVRLinTrain <- train( price_usd ~ ., data = train.data, method = "svmLinear",
                           trControl = trainControl("cv", number =10),
                           preProcess = c("center", "scale"),
                           tuneLength = 10
)

summary(modelSVRLinTrain)
#Length  Class   Mode 
#1   ksvm     S4 
modelSVRLinTrain$bestTune
#C
#1 1

# Predict using SVR Model with Linear Method
modelSVRLinTrainPrediction <- predict(modelSVRLinTrain, test.data)

# Prediction error, rmse
RMSE(modelSVRLinTrainPrediction,test.data$price_usd)
#[1] 3257.887

# Compute R-square
R2(modelSVRLinTrainPrediction,test.data$price_usd)
#[1] 0.7772176

Afterwords, the polynomial method was used with the SVR model:

# Create SVR Model using Polynomial Method
Method
modelSVRPolyTrain <- train(price_usd ~ ., data = train.data, method = "svmPoly",
                           trControl = trainControl("cv", number =10),
                           preProcess = c("center", "scale"),
                           tuneLength = 10
)

summary(modelSVRRadialTrain)
#Length  Class   Mode
#1   ksvm     S4                     
modelSVRRadialTrain$bestTune
#sigma   C
#10 0.001556481 128 

# Predict using SVR Model with Linear Method
modelSVRPolyTrainPrediction <- predict(modelSVRPolyTrain, test.data)

# Prediction error, rmse
RMSE(modelSVRPolyTrainPrediction,test.data$price_usd)

# Compute R-square
R2(modelSVRPolyTrainPrediction,test.data$price_usd)

Lastly, the radial method was used with the SVR model:

# Create SVR Model using Radial Method
modelSVRRadialTrain <- train(price_usd ~ ., data = train.data, method = "svmRadial",
                             trControl = trainControl("cv", number =10),
                             preProcess = c("center", "scale"),
                             tuneLength = 10
)

summary(modelSVRRadialTrain)
modelSVRRadialTrain$bestTune

# Predict using SVR Model with Radial Method
modelSVRRadialTrainPrediction <- predict(modelSVRRadialTrain, test.data)

# Prediction error, rmse
RMSE(modelSVRRadialTrainPrediction,test.data$price_usd)
#[1] 4752.231

# Compute R-square
R2(modelSVRRadialTrainPrediction,test.data$price_usd)
#[1] 0.5937837

Even though the SVR model did much better than the Linear Regression Model it was vital to investigate more models in an attempt to create an even more accurate model. The Decision Tree was a price candidate since it is incredibly robust and relies on very few assumptions. Its simpler nature also makes it a model that would be preferred over other models(such as Random Forest Regression or KNN).

Decision Tree Regression Model

model_DT_Train <- train(price_usd ~ ., data = train.data, method = "rpart",
                        trControl = trainControl("cv",number = 10),
                        preProcess = c("center","scale"),
                        tuneLength = 10)

summary(model_DT_Train)
# Plot the final tree model
par(xpd = NA) # Avoid clipping the text in some device
plot(model_DT_Train$finalModel)
text(model_DT_Train$finalModel, digits = 3)

#Decision rules in the model model_DT_Train$finalModel

# Make predictions on the test data prediction_DT_Train <- model_DT_Train %>% predict(test.data)

# Prediction error, rmse RMSE(prediction_DT_Train,test.data$price_usd)

 #[1] 3245.413

# Compute R-square R2(prediction_DT_Train,test.data$price_usd) 

#[1] 0.7529956

Random Forest Tree Model

random_forest_ranger <- train(price_usd ~ . ,
                              data = train.data,
                              method = "ranger",
                              trControl = trainControl("cv", number = 10),
                              preProcess = c("center","scale"),
                              tuneLength = 10
)

summary(random_forest_ranger)
random_forest_ranger$bestTune
plot(random_forest_ranger)


# Plot the final tree model
par(xpd = NA) # Avoid clipping the text in some device
plot(random_forest_ranger$finalModel)
text(random_forest_ranger$finalModel, digits = 3)

# Make predictions on the test data
rf_predict_ranger <- predict(random_forest_ranger, test.data , type='response')

# Prediction error, rmse
RMSE(rf_predict_ranger,test.data$price_usd)


# Compute R-square
R2(rf_predict_ranger,test.data$price_usd)

KNN Model

model_knn <- train(
  price_usd ~., data = train.data, method = "knn",
  trControl = trainControl("cv", number = 10),
  preProcess = c("center","scale"),
  tuneLength = 20
)

summary(model_knn$finalModel)
# Print the best tuning parameter k that maximizes model accuracy
model_knn$bestTune
#k
#1 5
# Plot model accuracy vs different values of k
plot(model_knn)

# Make predictions on the test data
knn_predictions <- model_knn %>% predict(test.data)
head(knn_predictions)
#[1] 9560.000 9000.000 4580.000 5648.494 8575.200 7720.000
# Compute the prediction error RMSE
RMSE(knn_predictions,test.data$price_usd)
#[1] 3693.127

# Compute R-square
R2(knn_predictions,test.data$price_usd)
#[1] 0.6802895

Compare results obtained using different ML methods

Our choices: Linear Regression Decision Trees SVR (Linear and NonLinear) Random Forest Regression KNN